{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3d03f633",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "177 µs ± 1.8 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
     ]
    }
   ],
   "source": [
    "normal_list=range(10000)\n",
    "%timeit [1**2 for i in normal_list]\n",
    "# 165 µs ± 1.09 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b06de81d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.38 µs ± 149 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np_list=np.arange(10000)\n",
    "%timeit np_list**2\n",
    "# 速度快了两个数量级\n",
    "# 3.07 µs ± 42.7 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "7901e476",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3. 3. 3. 3. 3.]\n"
     ]
    }
   ],
   "source": [
    "# *3 在numpy的操作呗运行在每一个元素上\n",
    "np_list=np.ones(5)*3\n",
    "print(np_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "6293e80d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 15)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# *3 普通的列表吧改操作认为是整体性操作\n",
    "normal_list=[1,1,1,1,1]*3\n",
    "normal_list, len(normal_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "2f8b37e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[-0.35706869,  0.24083053, -0.26707626],\n",
       "        [ 0.73392723,  1.60335735,  0.62149987],\n",
       "        [-1.35465161, -0.43579789, -0.43439911]],\n",
       "\n",
       "       [[-0.34670341, -0.70197492,  0.21383781],\n",
       "        [ 0.86708721, -0.55132192, -1.58518811],\n",
       "        [ 1.88740073,  1.39279321, -0.46914508]]])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros(100)\n",
    "np.zeros((2,3))\n",
    "np.empty((2,3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ce17e4fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0.],\n",
       "       [0., 1., 0.],\n",
       "       [0., 0., 1.]])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.eye(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "cf5db887",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones_like(np_list)\n",
    "np.zeros_like(np_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "4c861af8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3, 4],\n",
       "       [5, 6, 7, 8]])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=[[1,2,3,4],[5,6,7,8]]\n",
    "arr_np=np.array(data)\n",
    "arr_np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3486c48e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 0.11111111, 0.22222222, 0.33333333, 0.44444444,\n",
       "       0.55555556, 0.66666667, 0.77777778, 0.88888889, 1.        ])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 另一个常用的初始化方法\n",
    "np.linspace(0,1,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "9a520d78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 504)\n"
     ]
    }
   ],
   "source": [
    "#504=252 X 2 两年美股交易日总数\n",
    "stock_cnt=200\n",
    "view_days=504\n",
    "stock_day_change=np.random.standard_normal((stock_cnt,view_days))\n",
    "print(stock_day_change.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "5fb060dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.20518834  1.24160094 -0.07833942 -0.5892398  -0.37159789]]\n"
     ]
    }
   ],
   "source": [
    "#打印出第一只股票前五个交易日的涨跌幅情况\n",
    "print(stock_day_change[0:1,:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "63ddef0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.20518834,  1.24160094, -0.07833942, -0.5892398 , -0.37159789],\n",
       "       [-0.92731301,  0.69756031,  0.8587428 , -1.30864755,  0.759648  ]])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_day_change[0:2,0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4eeb022e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[-1.04342934, -0.02139873,  0.0200544 ,  1.28412433, -1.08401904],\n",
       "        [-0.20401638, -0.46913595, -0.49350543, -1.03195836,  1.22349155]]),\n",
       " array([[-0.20518834,  1.24160094, -0.07833942, -0.5892398 , -0.37159789],\n",
       "        [-0.92731301,  0.69756031,  0.8587428 , -1.30864755,  0.759648  ]]))"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# copy以防止应用值被修改\n",
    "tmp=stock_day_change[0:2,0:5].copy()\n",
    "stock_day_change[0:2,0:5]=stock_day_change[-2:,-5:]\n",
    "# b=tmp\n",
    "stock_day_change[-2:,-5:]=tmp\n",
    "# view result\n",
    "stock_day_change[0:2,0:5],stock_day_change[-2:,-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "d91e9c60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1.04342934 -0.02139873  0.0200544   1.28412433 -1.08401904]\n",
      " [-0.20401638 -0.46913595 -0.49350543 -1.03195836  1.22349155]]\n",
      "[[-1  0  0  1 -1]\n",
      " [ 0  0  0 -1  1]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[-1.04, -0.02,  0.02,  1.28, -1.08],\n",
       "       [-0.2 , -0.47, -0.49, -1.03,  1.22]])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(stock_day_change[0:2,0:5])\n",
    "#astype(int)将涨跌幅转换为int后的结果，可以更清楚的发现涨跌幅数据两端的极值。\n",
    "print(stock_day_change[0:2,0:5].astype(int))\n",
    "#2代表保存li\n",
    "np.around(stock_day_change[0:2,0:5],2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "e493aa0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[        nan, -0.02139873,  0.0200544 ,  1.28412433, -1.08401904],\n",
       "       [-0.20401638, -0.46913595, -0.49350543, -1.03195836,  1.22349155]])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp_test=stock_day_change[0:2,0:5].copy()\n",
    "tmp_test[0][0]=np.nan\n",
    "tmp_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "95848c07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[False False False  True False]\n",
      " [False False False False  True]]\n"
     ]
    }
   ],
   "source": [
    "mask=stock_day_change[0:2,0:5]>0.5\n",
    "print(mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "d6278f3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.28412433, 1.22349155])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp_test=stock_day_change[0:2,0:5]\n",
    "tmp_test[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "98ee898d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.04342934, -0.02139873,  0.0200544 ,  1.        , -1.08401904],\n",
       "       [-0.20401638, -0.46913595, -0.49350543, -1.03195836,  1.        ]])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp_test[tmp_test>0.5]=1\n",
    "tmp_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "86e83ae9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.20518834  1.24160094 -0.07833942 -0.5892398  -0.37159789]\n",
      " [-0.92731301  0.69756031  0.8587428  -1.30864755  0.759648  ]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 1.24160094, -1.30864755])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp_test=stock_day_change[-2:,-5:]\n",
    "print(tmp_test)\n",
    "tmp_test[(tmp_test>1)|(tmp_test<-1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "2d0f9a19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#np.all判断序列中所有的元素是否全部是true，即对bool序列进行与操作\n",
    "np.all(stock_day_change[0:2,0:5]>0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "8747d502",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#np.any判断序列中所有的元素是否有元素是true，即对bool序列进行或操作\n",
    "np.any(stock_day_change[0:2,0:5]>0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "36427b69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.20518834,  1.24160094,  0.0200544 ,  1.        , -0.37159789],\n",
       "       [-0.20401638,  0.69756031,  0.8587428 , -1.03195836,  1.        ]])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对两个序列对应的元素亮了比较，maximum()结果几去打，相对使用mininum()为取消的结果集\n",
    "np.maximum(stock_day_change[0:2,0:5],stock_day_change[-2:,-5:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f11fb181",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1  0  0  1 -1]\n",
      " [ 0  0  0 -1  1]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-1,  0,  1])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "change_int=stock_day_change[0:2,0:5].astype(int)\n",
    "print(change_int)\n",
    "np.unique(change_int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "6d2b994f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1.04342934 -0.02139873  0.0200544   1.         -1.08401904]\n",
      " [-0.20401638 -0.46913595 -0.49350543 -1.03195836  1.        ]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 1.02203061,  0.04145313,  0.9799456 , -2.08401904],\n",
       "       [-0.26511956, -0.02436949, -0.53845292,  2.03195836]])"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# axis=1\n",
    "print(stock_day_change[0:2,0:5])\n",
    "np.diff(stock_day_change[0:2,0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "8a66707e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 1 0 0 0]\n",
      " [0 1 1 0 1]]\n"
     ]
    }
   ],
   "source": [
    "#np.where()函数在数据筛选、改造中有非常大的作用\n",
    "tmp_test=stock_day_change[-2:,-5:]\n",
    "print(np.where(tmp_test>0.5, 1, 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "1a77e2d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.20518834  1.         -0.07833942 -0.5892398  -0.37159789]\n",
      " [-0.92731301  1.          1.         -1.30864755  1.        ]]\n"
     ]
    }
   ],
   "source": [
    "print(np.where(tmp_test>0.5, 1, tmp_test))\n",
    "# np.logical_or()\n",
    "# bp.logical_and()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "a493019d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#np.save可以将Numpy序列化持久保存\n",
    "np.save('./stock_day_change',stock_day_change)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "0d8cd594",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 504)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取数据np.load()，注意参数加上npy后缀\n",
    "stock_day_change=np.load('./stock_day_change.npy')\n",
    "stock_day_change.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "38d85d52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.04342934, -0.02139873,  0.0200544 ,  1.        ],\n",
       "       [-0.20401638, -0.46913595, -0.49350543, -1.03195836],\n",
       "       [ 2.22552678, -0.5385886 , -0.03411876,  1.83552911],\n",
       "       [ 1.22786868,  0.63687655,  1.1205846 , -0.29191998]])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_day_change_four=stock_day_change[:4,:4]\n",
    "stock_day_change_four"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "e9cbbb49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最大涨幅[ 1.         -0.20401638  2.22552678  1.22786868]\n",
      "最大涨幅[-1.04342934 -1.03195836 -0.5385886  -0.29191998]\n"
     ]
    }
   ],
   "source": [
    "# 横向的分析某只股票在4天内的统计信息，需要使用参数axis=1\n",
    "print('最大涨幅{}'.format(np.max(stock_day_change_four,axis=1)))\n",
    "print('最大涨幅{}'.format(np.min(stock_day_change_four,axis=1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "95a5720e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最大涨幅[0.7226866  0.30071526 1.18017313 0.60012211]\n",
      "最大涨幅[-0.01119342 -0.54965403  0.87208713  0.67335246]\n"
     ]
    }
   ],
   "source": [
    "print('最大涨幅{}'.format(np.std(stock_day_change_four,axis=1)))\n",
    "print('最大涨幅{}'.format(np.mean(stock_day_change_four,axis=1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e75f0b82",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最大涨幅[3 0 0 0]\n",
      "最大涨幅[0 3 1 3]\n"
     ]
    }
   ],
   "source": [
    "print('最大涨幅{}'.format(np.argmax(stock_day_change_four,axis=1)))\n",
    "print('最大涨幅{}'.format(np.argmin(stock_day_change_four,axis=1)))\n",
    "# axis=1 表示横向的\n",
    "# axis=0 表示纵向的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5f3fd10b",
   "metadata": {},
   "outputs": [],
   "source": [
    "a_investor=np.random.normal(loc=100,scale=50,size=(100,1))\n",
    "b_investor=np.random.normal(loc=100,scale=50,size=(100,1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "91861fb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a交易者的期望99.67, 标准差48.71, 方差2372.56\n",
      "b交易者的期望100.85, 标准差50.74, 方差2574.71\n"
     ]
    }
   ],
   "source": [
    "print('a交易者的期望{0:.2f}, 标准差{1:.2f}, 方差{2:.2f}'.format(\n",
    "    a_investor.mean(),a_investor.std(),a_investor.var()))\n",
    "print('b交易者的期望{0:.2f}, 标准差{1:.2f}, 方差{2:.2f}'.format(\n",
    "    b_investor.mean(),b_investor.std(),b_investor.var()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "c46cbed0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x12fe7cb80>]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_mean=a_investor.mean()\n",
    "a_std=a_investor.std()   \n",
    "# 收益绘制曲线\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a_investor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "924e6286",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "股票0 mean均值期望：0.009\n",
      "股票0 std振幅标准差：1.020\n"
     ]
    }
   ],
   "source": [
    "#正态分布 p62\n",
    "import scipy.stats as scs\n",
    "import matplotlib.pyplot as plt\n",
    "stock_mean=stock_day_change[0].mean()\n",
    "stock_std=stock_day_change[0].std()\n",
    "\n",
    "print('股票0 mean均值期望：{:.3f}'.format(stock_mean))\n",
    "print('股票0 std振幅标准差：{:.3f}'.format(stock_std))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "871d61e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x12fee0640>]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BV75j9GjnlEvLltCsme00rra5fE3WVI4kIvEcT2xcYDuO8hIt6Mo3HD0KEyc6y6nn0FXOGpd6Lr37DysodeaE5TTKG7SgK98wYoTTXbFzZ6hb13aagLCrVGWWX3sL4cnn6autdFfQgq7sO3AAPvjAmZRh+HDbaQLKhMYPkILQddvnlDt93HYcdYW0oCv7RoyApCTo3h2uu852moASXfxqFl9/K2EpSTz17TzbcdQV0oKu7Nq7F2bMgJAQGDIk8+2V1711y/0kSRCdflxDpVOXm11S+Tot6MquYcMgJQV69YIqVWynCUiHipRhQa0WBJsU+n8zx3YcdQV0kAyVay4dAbD67z/z2bx5EBYGL71kKZUCmNioK51+/JK7d69jUsMu7C1R0XYklQ3aQlfWDPhmtrPQpw+UL283TID7tWBJ5tRuTRCGp9fPsh1HZZMWdGXFDcf203L/Js6FhDtzXSrrJjXowrmQcFru38QNx/bbjqOyQQu6smJgaitw+k1toXRpy2kUQExEUefnwcWfj/IvWtBVrqt7ZBe3/vw9cWF5mVK/k+04Ko0p9TsRF5aXW3/+nsgjO23HUVmkBV3lur9bfx9EtuePfIUsp1Fp/ZGvEB9EtgfgmXUzdUJpP6MFXeWqhr9so9Gh7fwZnp8Pbu5gO45Kx7R6HTmdJ4IGh3+EL7+0HUdlgXZbVBdkNEHxwdFtvbMDY5xWH86f9rF5IrzzucqrzoTnZ2q9e3hu3QynO2nz5jqUsZ/QFrrKNbcdiKLur3s4mbcg02+6y3YcdRkf1W1HTL7C8N//wrJltuMoD2lBV7kjJeVC63xSgy78FZ7PciB1OefC8vBegy7OyssvO3fzKp+nBV3ljoULuf73AxyPKMqsOm1sp1EemF2nNZQtC9u2wSef2I6jPKAFXeW8pCSnlQe806gbCaHhlgMpTySEhF34uTFkiPNzVD5NC7rKebNmwd69/FK4NAtqtbCdRmVFr15QubIzKubs2bbTqExoQVc5KzERXnkFgDdvuZ/zwaGWA6ksCQ2FoUOd5VdecX6eymdpt0WVs6ZNg4MHoUYNltTQiZ/90gMPwGuvwZ498OGHzmBq5EI3V5Vl2kJXOefsWXj1VWd5+HBSgoLt5lHZExx8cWrAESPg3Dm7eVSGPCroItJKRPaKSLSIDErn9adFZJeIbBeRL0WkgvejKr8zaRIcOwY33QT33GM7jboSnTpB7drw668webLtNCoDmRZ0EQkG3gVaAzWA+0SkxiWb/QBEGmNqAZ8Ar3s7qPIzsbEwerSz/OqreqehvwsKclrnAKNGwZkzdvOodHnSQq8HRBtjDhhjEoF5QPu0GxhjvjLGnE1d3QSU825M5XfefBNOnoRbboFWrWynUd7Qti00agQnTsAbb9hOo9LhSUEvCxxOs34k9bmMPAysvJJQys+dPAnjxzvLI0dq69wtRC7+1TVuHMX+Om01jvonr14UFZHuQCQwNoPXe4tIlIhExcTEeHPXypeMGuWccrnzTmimPVtcpUkTp6UeF0ffjfNtp1GX8KTb4lEg7YSP5VKf+x8icgfwItDMGJOQ3gcZY6YCUwEiIyN1oGULMupq5jW//ELCW28TDrS9qi07c3p/Kkel932pXrIVK1jBAz+s5IPI9hwpXDrT94B2Z8wNnrTQNwPVRKSSiIQB3YClaTcQkTrAFKCdMeZ378dUfmPoUMKTk/i0RjN2lqpiO43KAXtKVuLT628lLCXp4kTfyidkWtCNMUlAX2AVsBtYYIzZKSLDRaRd6mZjgQjgYxHZKiJLM/g45WY7dsCMGSQGhTC+yb9sp1E56I3GD5AYFELHnWup/vvPtuOoVB6dQzfGrDDGXGOMqWKMGZn63BBjzNLU5TuMMaWMMbVTH+0u/4nKlV54AYxhdp3WHC6sEz+72ZHCpZldpzVBGJ5dN8N2HJVK7xRV3vH117B8ORQowDuNutlOo3LBxIZdiQvLS/OfNnPz4R9tx1FoQVfeYAw8/7yz/OyznNKJnwPCyfyFmZY6L+zzX0/XCaV9gBZ0deUWL3amKitVCgYMsJ1G5aL3b+7IybwFiTy6mzuiv7MdJ+BpQVdXJinJOXcOzjCrETrxcyD5KzwfExt1BeDZddMJSkm2nCiwaUFXV+bDD2HfPqhaFR55xHYaZcHs2m04XKgU1544xL3bv7AdJ6BpQVfZd/YsDBvmLI8c6UyGoAJOYkgoY5r1AGDg+llEJJzN5B0qp2hBV9k3bpwzPG5kJHTubDuNsmhZ9SZ8f1V1Spw9zWObPrYdJ2BpQVfZc+QIjBnjLI8f7wyvqgKXCK/e7pxye2Tzp5T78zfLgQKT/haq7Bk0yDnl0rkzNG1qO43yAT+Urc6S65oRnnye576ebjtOQNKCrrJu0yZnBvjwcBib7sCaKkCNubUH8SFhtNu9jpuO7rYdJ+DoJNEqa1JSoH9/Z3ngQKhY0WYa5WN+LViS92/uyJMb5/Pyl9Po+K9xmY6Hr6Mzeo+20FXWzJnj3ERUurRz2kWpS0yu34nf8xehzrG9tNu9znacgKIFXXnur78uFvHXXoMCBezmUT7pr/B8jEsdbfO5r/+P8PPpTo+gcoAWdOW511+Ho0ehbl148EHbaZQP++SG5uwqWYlysTE8HLXEdpyAoQVdeebQIaeggzMBtHZTVJeREhTMiNRujI9v+pgScacsJwoM+lupPDNoEMTHw733QuPGttMoP7Cxwo18UbU+EYnnGPzVh7bjBAQt6Cpz334Lc+dCnjwXW+lKeWB480eJDwmj46618NVXtuO4nnZbVJcVkpwEjz3mrAwcCBUq2A2k/MrhwqWZ2PBenlk/i+jOD9K61zucD9Yxf3KKttDVZT0UtRS2b3f6mw8ebDuO8kNT63Xip6JlqXrqCI9+t9h2HFfTgq4yVPbP3xmwIXVW90mTIF8+u4GUX0oMCeXlFs5feU9+O59yp49bTuReWtBV+ozhlS/eI9/5BOjSBVq3tp1I+bFvK9ZmyXXNyJuUwNAvp9qO41pa0FW6Wu7byB0/bSY2LJ/TTVGpK/Tq7Q9zJiwvLaK/o8X+TbbjuJIWdPUP+RPOMmz1FADGNnsQrrrKciLlBjERRRmfegfp0NVTyJsYbzmR+2hBV/8wcP0sysSdZGuZasyuradalPfMvKktP5aqQrnYGJ76dp7tOK6j3RbV/6h5PJoeW5aRJEEMbvkkKUHBGW6b0Sh5WeWtz/EngXjMAMlBwbx05+MsmvkMj2xezKLrb2N/Ce0K6y3aQlcXBKUkM2rVRIJNCh9FtmNXqcq2IykX2nrVtcyt3ZLQlGReX/k2wSnJtiO5hhZ0dcGDW5ZT63g0RwuUYELjB2zHUS42pllPjkUUo86xvfT+bpHtOK6hBV0BUOnUUZ5PnTZsWIt/czYsr+VEys1i80TwfOunAOj/zWyuiTloN5BLaEFXBKck88ayN8iblMDiGrfyRbUGtiOpALCucl3m3NiK8OQk3lg+wRlmQl0RLeiKxzZ9TJ1je/m1QHGGtuhjO44KICNv68XhQqWo+dtPPLFxge04fk97uQS4msej6bdhLgDPtOlPbJ4Iy4lUIPkrPB/Pte7H3HmD6btxPqur1mNn6aqAzjWaHdpCD2Dh5xOYsGw8oSnJfFT3br6tWNt2JBWANlaoxUd17yY0JZnxyycQlnTediS/pQU9gD23bgbVTh4mumg5RjfraTuOCmCvN+3Bz0XKUP3EL/T/e0A4lWVa0ANUw1+28XDUEs4HBTPgroEkhIbbjqQC2LmwPAxs8zTJEsS//7uIOkf32I7klzwq6CLSSkT2iki0iAxK5/WmIrJFRJJEpLP3YypvKhgfx7jlbwLwTqNu7ChTzW4gpYAt5a7j/Zs7EGxSmLBsPAUS/rIdye9kWtBFJBh4F2gN1ADuE5Eal2x2COgJzPF2QOVlxjBs9RTKnolha5lqTGrQxXYipS6Y0KQ7O0tWpuLpY4xd8SYYYzuSX/GkhV4PiDbGHDDGJALzgPZpNzDGHDTGbAdSciCj8qJu21Zxz86vOBcSztNtB5IUrB2dlO9ICAnjsQ4vEBuen1b7NvJw1BLbkfyKJ7/NZYHDadaPAPWzszMR6Q30Brj66quz8xHKQ+l1+brx170sWD0ZgBdbPs6BYuVyO5ZSmTpUpAzPtunHlMWjGLT2I34ocy1byl1nO5ZfyNWLosaYqcaYSGNMZIkSJXJz1wGv6Nk/mfTpaMKTk5hRpy2Laja3HUmpDK26phFTb+5IaEoy7y4ZTdGzf9qO5Bc8KehHgfJp1sulPqf8RHBKMm8vfZ2yZ2LYctW1jGj+iO1ISmXq9WY92Fy2BmXiTvLmf8YRpKMyZsqTgr4ZqCYilUQkDOgGLM3ZWMqbBq6fSeNfthGTrzCPdXiB88GhtiMplamk4BD6tn+OE/kK0fTgDzz57XzbkXxepgXdGJME9AVWAbuBBcaYnSIyXETaAYjIzSJyBOgCTBGRnTkZWnmu5b5veXzTJyRJEE+2f47fChS3HUkpj/1WoDj97n6WFIR+G+bS+OcfbEfyaR6dQzfGrDDGXGOMqWKMGZn63BBjzNLU5c3GmHLGmPzGmGLGmOtzMrTyTOWTRxi3fAIAo2/tyaara1lOpFTWbahYm7duuY8gDG//Zyzs22c7ks/SO0VdqkDCX0xePIoCiedYdm1jpt3c0XYkpbLtnUZd+bLKzRQ9FwutW8Pvv9uO5JPEWOq4HxkZaaKioqzs2xfk6Ehy8fFsvLYeDQ/tYH+x8nT413j+Cs935Z+rlEX5Es8xb+4L1DoeDfXqwZo1kD+/7Vi5TkS+N8ZEpveattDdJjkZunen4aEd/BZRlIe6DNNirlzhbFheHu40FCpWhO++g/vvd77v6gIt6G5iDPTtCwsXEhuenx5dXuFIoVK2UynlNTERRWDlSihSBJYuhaee0uEB0tCC7iYjRsDkyRAeziOdXmZPyUq2EynlfdWrO8U8PBwmTYKxY20n8hla0N1iyhQYOhSCgmDePL4rX9N2IqVyTuPGMHMmiMDzz8McHRcQtKC7w6JF8PjjzvJ770GHDlbjKJUrunSBceOc5Z49nVZ7gNOC7u8+/9y5OJSSAsOHQ+/ethMplXsGDICnn4bz56FTJ/j4Y9uJrNKC7s8WLoS77oKEBHjiCXjpJduJlMpdIk4r/dlnISkJunWDWbNsp7JGC7q/+ugjuPdep2XSvz+8/bbz5VYq0IjAmDEwZIjzl+qDD8KHH9pOZYUWdH/01lvQq5fz5X3lFXjjDediqFKBSsT5XRg50unG+PDDzvWkAKNVwJ8Y43xp+/d31t9802mVaMtcKcfgwTB+vLP8+OMwYYLdPLlMC7q/SElxLv4MG+a0xj/6CPr1s51KKd/z9NMwceLF5WefDZg7SrWg+4O4OLjvPqdFHhrqXMnv2dN2KqV81xNPwAcfQEiIc9G0bVv44w/bqXKcFnRft2ePMxDRggVQoAAsWwb33GM7lVK+r1cv+OILKF4cVq1yfo927bKdKkfplO85LKNRFT2ycKHTEo+LY1+xq+nTcTAH1pyHNVfwmUr5uSyNVHrrrRAV5dxst3UrNGjgdGts1y4nI1qjLXRflJQEzz0HnTs7p1u6dqXDg+M5UKyc7WRK+Z8KFWDDBujaFc6cgfbtnXGPUlJsJ/M6Lei+5rffoEULZ8Ch4GDnKv3cuZwNy2s7mVL+K18+mDsXXnvN6RU2ZIgzUcahQ7aTeZUWdF9hDO13fgU1a8LatVC6NHz1ldNFUbslKnXlRGDQIOc6VNGizrAZNWvCtGmuGYJXC7oPKPfnb0z/eChvLRsPJ07A7bfDli3QpIntaEq5T5s2zsXRjh2dUzCPPgotW7qita4F3aKglGR6bV7C5x88TrOft3A6T4Rzy/Lq1VCmjO14SrlXqVJOp4O5c6FYMac3TM2aMHWqX7fWtaBbct3vB1g06xmGrHmffOcT+E/1JtzxyHvw0EN6ikWp3CDiDOa1c6fTFfjMGfj3v6FpU9i40Xa6bNFui7ms0qmj9Nswh3a71hGE4dcCxXn5zsf4smp929GU8mtX1EW46kPc1a4qr3wxmWLffAONGjmnZEaNcmZI8vJ+vTIZfDq0oOeScqeP89S387jnxzWEmBQSg0KYVacNbzTpTpxO4qyUXSIsu64pX1euy45825zeZYsXw5Ilzg1Kw4ZB2bK2U2ZKT7nksNKxJ3h11bt89f6/uXfHagDm1rqT23pPZfgdvbWYK+VDzoTnd0ZsjI52Tr+IOL1gqlaFgQPh4EHbES9LC3pOMAa+/hq6dWPdlEfovnUlQcaw8PrbaP7oZF5o/RRHC5W0nVIplZGrrnImXN+1y5nqLj7eGaa6ShXnrtMvv/TJi6d6ysWb/vgDZsxwvgh79gAQLEEsq96ECbfcz0/Fy1sOqJTKkmuuccZR2rLFOQ0zf75zGmbJEqhRA/r2JV9iCZ+58U8L+pVKSIA1a5wf9Pz5zv/Jwel2+OijNI6pxLGCJexmVEpdmZtugpkznZEbp0692Hp//HG+C8vL6qr1WHFtY76udBMJoeHWYmpBz47YWFi5Ej79FJYvd7o7/e3OO6FPH2euz9BQjl3JlXellG8pVQpeftm543TRInjnHSI2bKDDrq/psOtr4sLysqbKzSy/tjFrK9fN9eIuxtJ5oMjISBMVFZWt92ZptDVvSE6Gbdtg3TrnduEvv4TExIuv16rFmwWuZ/H1t/FLkatyJoNSKldktY40/fc0Wu/bQJs9G7jx+P4Lz58NDWdzuevZeHUtNl59Az+WrkpyUHC29pGWiHxvjIlM7zVtoacnPt4ZcnP9eqeIb9jwv61wEWjc2Omn2qEDVK7Mm9oSVyogHSpShin1OzOlfmfKnT5Om70baLP3G2of20+zn7fQ7OctAMSG5WNz+evZePUNsK0c3Hij17MEdkE3Bo4ccVrf27dffOzd+8+hNStXdu4ga9rUGQuiVCk7mZVSPutI4dJMrd+JqfU7USLuFA0P7aDBoe00PLSdSn8co/lPm2n+02Z4/ih89pnX9+/ugm6M07I+dszpP3rgAPz0k/Pv34+0Le+/BQc74zo0aeIU8CZN/OKmAqWU74iJKMrSGs1YWqMZAGViY2h4aDsNf9lBl86dc2SfHhV0EWkFvAUEA9OMMaMveT0cmAHUBU4CXY0xB70bNdUff1Dx1FEKx8dR+NwZCsWfoVB8HIXj46Df507xTvs4e/byn1esmPOnT61aF/+tUQPy5MmR+EqpwHSsYAkW1WzOoprN6fKIpVv/RSQYeBdoARwBNovIUmNM2sn5Hgb+MMZUFZFuwBiga04EpnNn1q5Zk/5r36TzXN68ThfCChWcmwIqV774qFIFihTRwbCUUq7gSQu9HhBtjDkAICLzgPZA2oLeHhiWuvwJMFFExOREF5oKFThYuAyn80YQGx7B6bwFOJ2nAKfzRPBUl/rOxBBlylz8t2BBLdhKqYDgSUEvCxxOs34EuHRowAvbGGOSRORPoBhwIu1GItIb6J26Gicie7MTGoDT/3yq38b5mb2r+KWZ/JRbjgPccyx6HL4nW8ciY3IgyZXt49LjqJDRhrl6UdQYMxWYmpv7TEtEojLqv+lP3HIc4J5j0ePwPW45lqwchyeDcx0F0g5CUi71uXS3EZEQoBDOxVGllFK5xJOCvhmoJiKVRCQM6AYsvWSbpUCP1OXOwJocOX+ulFIqQ5meckk9J94XWIXTbfFDY8xOERkORBljlgIfADNFJBo4hVP0fZG10z1e5pbjAPccix6H73HLsXh8HNbGclFKKeVdOsGFUkq5hBZ0pZRyiYAr6CIyQkS2i8hWEflcRPxyvFsRGSsie1KPZbGIFLadKTtEpIuI7BSRFBHxyy5mItJKRPaKSLSIDLKdJztE5EMR+V1EfrSd5UqISHkR+UpEdqV+r/rZzpRdIpJHRL4TkW2px/JKpu8JtHPoIlLQGBObuvwUUMMY08dyrCwTkTtxehMliTi3KRhjnrccK8tE5DogBZgCPGOMyd4g+ZakDo2xjzRDYwD3XTI0hs8TkaZAHDDDGFPTdp7sEpEyQBljzBYRKQB8D3Twt58HgIgIkN8YEycioTiDm/QzxmzK6D0B10L/u5inyg/45f/RjDGfG2OSUlc34dwf4HeMMbuNMdm/Y9i+C0NjGGMSgb+HxvArxph1OD3U/Jox5pgxZkvq8hlgN86d7H7HOOJSV0NTH5etVwFX0AFEZKSIHAYeAIbYzuMFvYCVtkMEqPSGxvDLAuI2IlIRqAP813KUbBORYBHZCvwOfGGMueyxuLKgi8hqEfkxnUd7AGPMi8aY8sBsoK/dtBnL7DhSt3kRSMI5Fp/kyXEo5U0iEgEsBPpf8le5XzHGJBtjauP8BV5PRC57OsyVE1wYY+7wcNPZwApgaA7GybbMjkNEegJ3Ac19+c7cLPw8/JEnQ2OoXJR6vnkhMNsYs8h2Hm8wxpwWka+AVkCGF65d2UK/HBGplma1PbDHVpYrkTrpyHNAO2NMJrN4qBzkydAYKpekXkj8ANhtjHnDdp4rISIl/u69JiJ5cS68X7ZeBWIvl4XAtTg9K34B+hhj/K5FlTrMQjgXB0Hb5Ke9dToC7wAlcAZF3mqMaWk1VBaJSBvgTS4OjTHSbqKsE5G5wK04Q7X+Bgw1xnxgNVQ2iEhjYD2wA+d3HGCwMWaFvVTZIyK1gOk436sgYIExZvhl3xNoBV0ppdwq4E65KKWUW2lBV0opl9CCrpRSLqEFXSmlXEILulJKuYQWdKWUcgkt6Eop5RL/D+eLNqyGSey3AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(stock_day_change[0], bins=50, density=True)\n",
    "fit_linspace=np.linspace(stock_day_change[0].min(),stock_day_change[0].max())\n",
    "# 由均值、方差来描述曲线，使用scipy.stats.norm.pdf生成拟合曲线\n",
    "pdf=scs.norm(stock_mean, stock_std).pdf(fit_linspace)\n",
    "plt.plot(fit_linspace, pdf,lw=2,c='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "9ad5a7b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0022022 , 0.00322726, 0.00466071, 0.00663298, 0.00930264,\n",
       "       0.01285711, 0.01751139, 0.02350379, 0.03108817, 0.04052215,\n",
       "       0.0520511 , 0.06588815, 0.08219109, 0.10103741, 0.12239951,\n",
       "       0.14612254, 0.17190747, 0.19930231, 0.22770362, 0.25637022,\n",
       "       0.28444954, 0.31101614, 0.33512023, 0.35584298, 0.37235413,\n",
       "       0.38396707, 0.39018612, 0.39074163, 0.38560937, 0.37501228,\n",
       "       0.35940444, 0.33943875, 0.31592168, 0.28975935, 0.26190002,\n",
       "       0.23327791, 0.20476312, 0.17712093, 0.150983  , 0.12683125,\n",
       "       0.104994  , 0.08565304, 0.06885905, 0.05455309, 0.04259099,\n",
       "       0.03276846, 0.02484474, 0.0185632 , 0.0136682 , 0.00991768])"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "0855f783",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-51.29778047 -45.76364454 -45.67988407]\n"
     ]
    }
   ],
   "source": [
    "keep_days=50\n",
    "stock_day_change_test=stock_day_change[:stock_cnt,0:view_days-keep_days]\n",
    "#stock_day_change_test\n",
    "print(np.sort(np.sum(stock_day_change_test,axis=1))[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "5be68e83",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "买入第[93 85 52]只股票， 从第454个交易日开始持有盈亏：2.38%\n"
     ]
    },
    {
     "data": {
      "image/png": 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xFNW2cKZ6WuSBGjf53l7SrPgwQoKcpEWHqJyMiIyYglMfSo5yUVp3Njg9XFxPQ2snP3j+WM+yotqWAYftNrZ1nt23pB6AN3IruOPPu7jzb3vGqNUiIiJT38Ycz7xTlZTxrZOVTQQ5HaRGhwCQlRCu4FRERkzBqQ8lRbqobGynvdPN3oJa/rT1FADVTe0921z+49e459UT/e7fO4vgtpOeYuE/25QLwM7TNZS/bciwiIiIDE1WfBjJkS6VlPGx/IomZsSF4nR4hkpnJ4RxsqIJt1v5M0Rk+BSc+lBKlAuA8oZW3v3LzTxzoJTQICcXzUnos90Pnz/Wb+9p7+CzqtETqBbUNLM0IxqAV5QJWEREZESMMWzIiWPLiUoFTj6UX+nJ1NstOyGclo6uPtOcRESGalTBqTHmvcaYQ8YYtzFm1dvW3WWMyTPGHDPGXD26Zk4OSZGe4LSw5uz80Ob2Lr777kV8810L+my7p6D2nP3Le/Wc1jS30+W2VDa2syE7jrAgJ0dKGkbctu89c4R133tpSBmDRUREpqKN2fHUNHf0TJ0Zreb2zsE3msK63JbTVc3MSjgbnGZ5X2tor4iMxGh7Tg8CNwKv915ojFkA3AIsBK4B7jHGOEd5rgmve77Fy0fP9nDeeVkOGbGhfGzjrD7bnuin5Ex3cJoQEUxNUwfVTZ4ANTnSxdzkiBHfTFs7uvjDm/mU1rfy+zfzR3QMERGRya573qkv6p1++8lDrPnuS9M6YWFxbQvtXW6yevWc5nSXk6lQxl4RGb5RBafW2iPW2mP9rLoB+Lu1ts1amw/kAWtGc67JIDshnKiQQO59/SQAL335Yr501dye9Q98ci0Pf3oDwDklZ7rcloqGNoKcDmbFhVHd3E55g2ebxIhg5qdEcqSkfkQ1UA8V19PptixJj+Kt/GoKlKlQRESmoeQoF9kJYWwe5bzT+7ec4r7Np2hs6+SfOwt81LrJ52R3GZn48J5lCRHBRAQHqOdUREZkrOacpgG9P60LvcumNKfDsD4rDoD48CBmxYX1Wb8hJ56VM2KIDg3sMxfjlWPlrP7uJp4/VEpCRDAxYYHUNrf39KQmRnqC04bWzj5Dhodqr3cI8V3XzgeUqVBERKavjTnxbM+vpr3TPaL9Xz1WzrefPMQV8xO5ICeef+4ooGuazmHN9wagveecGmPISlTGXhEZmUGDU2PMJmPMwX5+bvBFA4wxdxhjdhpjdlZUVPjikH518VxP8qO7rp2Pw9F/ke/kSBdl9Z7As8tt+d7TR6huaie/somVM2KIDQuipK6V1455rkdihIsFqZEAHBnB0N59BbWkRLlYlxVLXFgQO0/VjORXExERmfQ2ZMfT0tHFnjPDvxceK23gXx/Yw9zkSH52y3I+uDaT4rpWXj8++b+/jER+ZRMRwQHEhwf1WZ4dH6ZhvSIyIoMGp9baK6y1i/r5efw8uxUBGb3ep3uX9Xf8e621q6y1qxISEvrbZFJ536oMnr7zAm5amT7gNomRrp5hvbnlDeSWN3LTinRuWpHO925cTHRoEA2tnfxxyynAM0RmXnIExtCTFGmwp7T1rR18/I87OFpaz96CWpamR2OMYcWMGHadrvbNLysiIjLJrM+Kw2Fg84nhDe2tbGzj43/cQWiQk99/dBVhwQFcsSCJ+PBgHth+ZoxaO7GdrGxiVkIYxvR9GJ+dGE5JXWuf+u0iIkMxVsN6nwBuMcYEG2NmAbOB7WN0rgnF6TAsTI067zbJkcGU1nmC03zvk8WPbZzJj9+3lPDgAGJD+z6BdAU6CQ0KYGZcGIdL6vjPRw+Q/Z/P8OLhsgHP8ejuIl4+Ws7PX8rlTHUzyzKjAVg1I4ZTVc19aqqKiIhMF1GhgSxOi2LLMKa4tHZ0ccefdlLV1MbvPrqqJwFioNPBe1el8/LR8nNySUwHby8j0y3bm7E3X72nIjJMoy0l8x5jTCGwHnjaGPM8gLX2EPBP4DDwHPBZa23XaBs7VSRHuqhsbKOzy90rmcDZD/fo0MCe19++fmHP6/kpEbxwuIwH3vI8od1bcO6QpFeOlfOj549xv7fX9ZkDntIxy7y1UlfNjAFg12kN7RURkelpQ048ewtqh9SzZ63lKw/tZ/eZWv73fctYkh7dZ/0tqzPoclsenGaJkVo7uiiqbek3OM3yZuzVvFMRGa7RZut91Fqbbq0NttYmWWuv7rXuu9babGvtXGvts6Nv6tSRFOXCbT2lY05WNJEUGUxYcEDP+lZvkoYbl6fx0Q0ze5ZfkJNA72S9BdV9kyO9mVvJx/+4g1+8kkdpfSu39dp3cZqnN3dhahRBToeG9oqIyLR1QU48nW7L9vzBh/b+dFMuT+wr5t+vnsu1i1POWT8jLoyNOXH8bXsB7mmUGOlMdTPW0m9wOiMuFIeBkwpORWSYxmpYr5xHdw2wY2UN5Fc2ktUrBTvAFfMTSY8J4TOX5vRZ/t5V6RgDcWFBrM+K43R1M+W9hhE9tKuAmNAgXv23S3jzq5fxresX8vSdF/DoZzb0BL+uQCeL06PYqZ5TERGZplbOiCEowDFoSZnH9xbxs5dyuWlFOp+5JHvA7T6wJpOi2hbemEbZ8LsTHr39OwxAcICTzNhQTmhYr4gMk4JTP5jvzby7+3QNuWWNzEro+9QxJSqEN796GTmJfT/wA50Odn39Sp77wkVkxIawr6CWNd97iU2Hy/jeM0d4bG8xl81LZGZ8GLFhnnmrC1OjWJ4Z0+c4c5IixrzWaZfbjiizsIiIyFhzBTpZNSOGzQMEk3UtHXz9sQN84R97WTMrlu/fuPicpD+9XbkgidiwIP721vRJjJTvnZY0Mz603/XZCSonIyLDp+DUDyJdgaTHhPB/L+fR0NbJe5YPvQRsbFgQCRHBZMScvRl8+cF93Pv6SQDe2c+Qo7eLDg2krqUDa8du+NF3nj7MtT97Y8yDYBERkZHYmBPP0dIGKhvPJgi01vLkvmKu+MlrPPDWGW7bMJM/3LaaoIDzf10KDnBy88p0Nh0po7xheiRGyq9sJCEimAhXYL/rsxLCyK9smrY1YEVkZBSc+klSpAuAqxYksXpm7LD3dwU6e17XtXQA8N33LOLSeYmD7hsdEkhHl6W53bc5qiob23qyFd63+RRw9smqiIjIRLIxJx6ALd6SMmeqmrntvh187m97SIoM5vHPXsA337WQ8F45Ic7nltUZdLotD+0qHLM2TyQDZertlp0QTlunm+LalgG3ERF5u6F94orP3X7hLFKjQ7j7xsUj2v89K9I4VFzHsoxovvXkYcBTWHwookI8TzlrWzr6JGIaqV2na3jpSBn3vHqClCgXj35mY8+609XNdHa5cRiDwzHwkCgREZHxtDgtighXAK8eK6ewppmfbcolwGH4xnUL+Mj6GQQ4h/f8PishnLWzYvn79gI+dVH2lL/n5Vc2ccX8pAHXZ3unJuVVNJIR2//QXxGRt1Nw6ifXLErhmkWDD8EdSHx4MD+9ZTn7CmoBcBhI89ZdG0x3qZq65o4h7zOQ/MombvrVFgBcgQ5K6lr5zesnetafqWoi52vPcvPKdH703qWjOpeIiIivOB2GdVlxPLK7CICrFybxresXkhI18vvirWsz+fzf97LlRBUXzB7aA+PJqK6lg8rG9vP2nGZ5150ob+TSuYOP6hIRAQ3rnfRmej/8U6NDBp0T0y2yp+e0fdTnf3JfMQAPfHIt+755FVEhgT1DemPDgjhU7EmKNF2GOYmIyOTxvlUZLEiJ5LcfWcVvPrxqVIEpwNULk4kODeRvO6Z2YqRT/dRof7vYsCCiQwN76rmLiAyFgtNJLiokkLiwIGbEDX3ITHSIJ5NvvXeu6kCstfx52+kBkxq53ZbH9haxZmYsG3LiCQ5wsjEnDoAIVwDLM6J75vIAPk2K8LVHD/Dh3781rWrKiYiIb125IIlnPn8hVy4YeHjqcLgCndy4PJ0XDpX2SbQ01XTnk8hKGDg4NcZ4MvaWK2OviAydgtMp4PNXzOa2DbOGvH33sN7a5vMHp6eqmvl/jx3kvs2naO3ooqapb0/rC4dLOVnRxK1rM3uWLc/wlK2JdAWe80Q1z4c3qL++dYY3civ5584Cnx1TRERktD6wJoOOLsvDU3jE0MnKJhyGQeeSZieEqdapiAyLgtMp4CPrZw7rqW93QqTuLL9ut6Wh9Wygaq2ltaOLLSc89d92n6nh3x7cx/L/fpH2TnfPdn/ZdobM2FDetTS1Z9mKGdEA1Da3s2JG3/qqB4rqhveLDeF32H6q2mfHFBERGa3ZSRGsnhnD33cUjGnJNn/Kr2wiPSaU4ADnebfLSginsrGt5/uGTF6nq5pY//2X2OvNdSIyVhScTkOhQZ6byfefPcpftp3m6p++zqU/eq0n8PzG44dY8I3neO1YBQCHiut4an8JAC8dKQM8Q3T3nKnhkrkJOHtlJFyYGgXAB9Zk9imRE+R0kFve4JP2t3V29dzoSuumRz05ERGZPG5ZnUl+ZRPbTk7NB6j5lY3nnW/aLTvBk7H3ZIWG9k52/9hRQEldK/+Y4vOpxf8UnE5DxpwNJr/+2EFyyxupbGxj28kqimpb+PO207gtvHy0nJhQT03Ubk94EyAdK22gqb2LFZl9e0ddgU4OfOsq7nrHfBIignuWz4wPJa9sZDenhtaOPkXNKxvPDi8uUXAqIiITzDuXpBARHMCT+4v93RSfs9aSX3H+Gqfdsr1zUjW0d3LrctuerNbPHSylo8s9yB4iI6fgVEiMCCY0yMnzh0p57mBpz/JOt+W9qzL6bHu6qhlrPYmQAFa+beguQIQrsKc39f6Pr+H+j68hJzGcvBE+Ob3mp2+w5rsv9byvaPAkmchKCKO4tmXKDpsSEZHJyRXoZHZSOPlTMCiraGijqb3rvMmQumXEhhLgMOo5neTezKuktL6VG5enUdPc0SfZpYivKTidpn703qWsy/IMu71kbgKXzk3kuYOlvH68gsRePZ4XzU4gI9aTWj/I6aC8oY3H9xZz7+snuXB2POkx50+7f/GcBC6ek0BOQjgF1c20dnQNq50dXW6KalsAaO3oorWji2cOeIYYL0uPpq3TTU2vxE4VDW184o87KKtXj6qIiPhPZmwoZwbIdj+ZnRxCGZlugU4HM+JCOaHgdFJ7aFchUSGBfPuGhUQEB/DUvqk3IkAmDgWn09TNK9P5+jsXALAxJ573LE+jqqmd145XcPn8JNKiPUHn/JQIVnqH7q6aGUNVUxsP7y4kLTqE+z+2ps8Q4fPJTgzHbeFU1fCeIu85U9vzOr+yiV+9eoJ7Xz8JwJJ0z/zWYm/wCvDi4TJeOlreE8CKiIj4Q2ZsKCV1LX0SCU4F+cMITsEz71TDeievupYOnj9Uyg3LUolwBXLlwiSeP1Q65f6uZeJQcDqNLUqL4tHPbOBdS1K5eG4CadEhBDoN1y1JYXZSOMmRLuLCg9mYE09QgIP1WXFYC2/kVnLdkhQcjqEFpgAz4zw3sTNVw3uK/OLhs8OMr/3ZG/zspdye94u9wel1//cm923O57E9Rdzzah4Am/Mqh3UeERERX8qIDcVt+z5AnQryK5sICnCQGnX+kVPdshPDOV3VRKfmKU5KT+0vpr3Tzc0r0wG4bkkK9a2dvJlX4eeWyVQV4O8GiH8t9/aKOjC8+KWLcDoMwQFO4sODqW32JB66aUU6F89JYE+v9OEXz00Y1nm6h/8W1gz9Jn2iopH7Np/iwtnxvJHbN9gMcjqYnxLJmpmx1Ld28O0nD/dZv+1kNZ1dbgKcev4iIiLjr7sGaEFNMzOH2Ms4GZysaGJWXNiQH1BnxYfR0WUpqGkZcm+rTBwP7SpkTlI4i9M8HQIX5CQQ6Qrgqf0lXDZv6GUMRYZK39ylR2hQQE/NsrnJEazNigPA4TAkRrr6zEVd5P2QGqrYsCBCAp1DDk5rmtq5/Mev0em2fGBNZp91t67N5OC3ryY0KIB/fmo9v79tdZ/1a2fF0tjWyalh9tJ2+89HD/Di4bIR7SsiIgKeYb3AlJt3OtQyMt2yEz3lZE6Ua97pZJNX3sieM7XcvDK9ZxpXUICDqxcm8+KhsmHnEREZCgWnMmSJka6e15GuwGHta4whPSaEwpqh3aRPe2/mN61I55qFyTz3hQu5bcNMACKCAwgKOPunmxYdwrKMaBIjgjn47au56x3zgZHVVWvt6OKBt85w+592DntfERGRbkmRLoKcjikVnHZ2uTlT3cysIWTq7ZYd7w1OlRRp0nloVyFOh+Hdy9P6LL9uaSoNbZ3njGoT8QUN65UhSwgPHnyj8/AEpy243XbQ4UDdc3Q+ccEsHA7DvORIvnzVHBrbOvnEhbPO2f6n719Gc3sX4cEBPent/7jlFPERwefUYh3KeQGOlNQzPyVyyPuKiIh0czo8D2ULplBwWlTbQkeXHVbPaVRoIPHhQZxUUqRJpctteXRPIZfMSSAxwtVn3YbsOGJCA3lqfzFXLtDQXvEt9ZzKkAUFOLjjoiwe+OTaEe2fERtKQXUz6+9+if/32EHaO8+WiXm77iCxO2sweOqn/ui9S8/5kASYGR/GglRPIBnpCiQiOIAtJ6q48Z4tw2pjce3ZEjQ7T9cMa18REZHeMqZYOZnuMjJZw5w7mpUQrp7TSeaN3ArK6tt6EiH1Fuh0cM2iZDYd1tBe8T0FpzIs//mO+WzIiR/RvkvSo2lo66Ssvo0/bzvN6u9uYuPdL1Pd1H7OtsW1rYQFOYkMGVnnfkNbZ8/r7fnVLP7m85TUDT7ftaj27JeIkimWYVFEpJsx5svGGGuMGdkHugxJZmzosLPUT2T5FcMrI9MtW8HppPPQrkKiQwO5bH5iv+vfuTiVpvYuXj1WPs4tk6lOwamMm3cvS+3zvq6lAzhbM6234toWUqNDhlxH9e2+eMUcwNPbe/+WUzS0dfLkvmKKalsG7K0FKKptxRhIjnRNufT/IiIAxpgM4CrgjL/bMtVlxIZQ39pJXXOHv5viE/mVTUS6AogNCxrWftkJYdQ0d/T7MFomnrrmDl44XMYNS1N7EmW+3bqsWOLCgnhqv+rKi28pOJVxE+B08Pq/X8p/37Cwz/L+kiQV17WQEj20Gmr9+fwVs/nGdQto73RTWu8Zqvv8oTKu+/kbbLz7ZT55/w6a2zvP2a+opoWkCBeZsaEU17Wes15EZAr4X+ArgPV3Q6a6zF7lZKaC/MomZiWED/vBcXaCJynSSBIVyvh70lvb9L2rMgbcJsA7tPelI+X9fp8SGSkFpzKuMuNCee+qDBamRvKT9y0F6HfIU1FNC2nR584tHY5U7/67vHNHd52uoaa5g6UZ0Ww6Us7Tb3va53ZbjpTUkxYTQmq0ek5FZOoxxtwAFFlr9/m7LdNBxhQrJ5Nf2TTs+aYA81IiMAZ+8uJxGlqnRi/yVPbQrkLmJUewMPX8SSGvW5JKS0cXrxytGKeWyXSg4FTGnSvQydN3XsiNK9JJiAg+54lyY1snVU3tPTf1kUqJOtvz+i8XZfW8fuhT60mNcvHcwdKeZc3tnXz5wX0cLqnnvSvTSYkOoay+lS63OhZEZHIxxmwyxhzs5+cG4D+BbwzhGHcYY3YaY3ZWVOiL50hNpeC0taOLotqWYc83Bc/9+Ic3L2V7fjXv+802yuo1MmmiyitvYG9B39qmA1kzK5aEiGCe2l88Tq2T6UDBqfhVZj+ZDLt7UmfEDv8G2Ftqr2HBVy1M5oFPruXPn1hDoNPBVQuTeSO3kvZONwAP7izk0T1F3H7hLN6/OoPU6BA6uiyVjW2jaoOIyHiz1l5hrV309h/gJDAL2GeMOQWkA7uNMcn9HONea+0qa+2qhISE8f0FppBIVyAxoYFTIjjNLfMMyR1JcApw88p0fn/bak5XNXHjPVvIK9cQ34noQW9t0xuWpQ26rdNheMeiZF4+Wk5Tm4b2im8oOBW/yowNJb+yCWvP9lCeqfYkSJoRN7qe07iwICKCA7h2UTIrZ8SwISeeC2d7vmTNT4mgvctNeYPn6e3pqmZCg5z85zvmY4whNcozJFhDe0VkqrDWHrDWJlprZ1prZwKFwAprbekgu8oodJdRm+xePFKGw8D67LgRH+PiOQn84471tHV2cfOvt7DzVLUPWyij1dnl5tHdRVw6N4GEiKHVtn/nklTaOt1sOlI2xq2T6ULBqfjVyhkxlNW3caJXce7uJ8yjHdbrcBh2fP0K7vnginPWJUZ6gs/uoUUFNc2kx5zNDtzd69q77qmIiMhwTZXg9NkDJayeGUt8+NCCloEsTo/ikU9vJCY0iA/+7q0+U2zEv97Iq6S8of/apgNZNSOGpMhgZe0Vn1FwKn51yVxPT2bvOlmnq5qJDg0kKiRw1Md3BTr7nTOR3BOceobtFlQ3kxFzNhhO9c5XLalrwVrLMwdKyCtv5HTVuWVvREQmI28PaqW/2zHVZcaGUljTMqlzGOSVN5Jb3si1i84ZAT4imXGhPPzpDcxPieTTf93Fn7ee8slxZXQe3V1ETGggl81LGvI+DofhHYtTeO1YhZJdiU+MKjg1xvzQGHPUGLPfGPOoMSa617q7jDF5xphjxpirR91SmZLSY0LJTgjjzTzP9yNrLbtO1zAzbnTzTQeT5A1OS+tasdZSVNPSp6c2MiSAsCAnRbUtvHKsnM/8dTdX/OQ1LvvxawpQRURkyDJjQ+l0W0rqJu80kecOenrFrlmU4rNjxoYF8bfb13H5vET+3+OH+PlLuT47tozMrtM1bMyJJyhgeOHBdUtSae9y8+JhDe2V0Rttz+mLwCJr7RLgOHAXgDFmAXALsBC4BrjHGNN/FV+Z9pZlxHCouJ665g6++I+9HC1t4INrM8f0nDGhgQQ5HZTVt1LX0kFDWyfpMWcTKBljSIkOoaS2lZ9tyiXAYbh5ZTpdbsuftp4e07aJiMjUkTkFMvY+e7CUFZnRJEeNrsTb24UEOfn1h1Zy1YIkfvFKXk+SQhl/lY1tFNW2sCQ9atj7Ls+IJjXKxZP7lLVXRm9Uwam19gVrbXd6rm14Mv8B3AD83VrbZq3NB/KANaM5l0xdC1IjqWho457X8nhsbzEXzUngPcsHzxI3GsYYEiODKatv7ckYmB7Td45ranQIhbXNHC6p55MXZvGj9y7l3ctSeeCtM1Ni/pCIiIy97uB0st43zlQ1c6i4nmt92GvaW4DTwbuWptLe6eZ4WcOYnEMGd6CoDoDFadHD3tfhfYD/yrEKjpTU+7hlMt34cs7px4Fnva/TgIJe6wq9y0TOsSDFU+T5N6+dZHZiOH/6+BoCnGM/HTo50kVpfSuP7CnCFeg4JwNhapSLg0X1dHTZni8XX7lmHg4DP92k4UciIjK4lCgXToehoHpyDut97lD3kF7fzDftz7KMaAD2FtSO2Tnk/A4WeoLTRWmRI9r/ExdkEeEK4McvHPdls2QaGjQCGKSYd/c2XwM6gb8OtwEq9C0LUs9+EF48Z/zq6c2MD2P3mVoe3lXIOxannJOAKbNXKZvu4DQ1OoSVM2P1dFdERIYkwOkgNdo1aYf1PnOglEVpkaPOoH8+6TEhxIYFsU/Bqd/sL6ojKyGMCNfIklFGhQZyx4VZbDpSpocMMiqDBqcDFfO21j4OYIy5DbgO+KA9W6yyCMjodZh077L+jq9C39NcVEggd107jzlJ4bx7jIfz9vbVa+Zx1YIkrpifxFeunnfO+mXp0T2vM3vdlNNjQihS/VMRERmizNjQSRmcltS1sLegdsyG9HYzxrA0PYp9hbVjeh4Z2IHCOhanDX++aW8fu2AWMaGB/PiFYz5qlUxHo83Wew3wFeB6a23vT90ngFuMMcHGmFnAbGD7aM4lU9u/XJzNC1+8mEWj/GAcjoSIYH5x6wp++cEV/SZ5WOIdZgSQEn12fXpMCNVN7TS1dZ6zz3DlVzbhnsTlBUREZHCZk7TWaXcN0rEc0tttaUY0ueWNNPrg3irDU97QSml966iD0/DgAD59STZv5Fby1skqH7VOppvRTuz7BRABvGiM2WuM+TWAtfYQ8E/gMPAc8FlrbdcozyUyrsKDA3peB/aaA9udOGm0vad/2nqKS3/0Kve8mjeq44iIyMSWERtKVVP7pAu8nj1YypykcLITwsf8XEszorEWDnoT80wElY1tdHRN/QzC3dd8Sa8RYyP14XUzSYwI5scvHOfsgMrz23mqmieU6Ve8RputN8dam2GtXeb9+VSvdd+11mZba+daa58933FEJqqff2A533n3oj7L0qI9JWeKajzB6e/eOMnv3jg5rOPWt3bw3aePAHDf5lPT4uYnIjJdZcRMvoy9FQ1t7DhV7dPapuez1BsY+XveaXN7Jw/vKuSWe7ey6jubuPvZo35tz3jYX1iHMbAwdWTJkHoLCXLyr5flsP1UNW/kVg66/e4zNXzo92/xb//cR0u7+rHEt9l6Raac65em8qF1M/osy/DWQy2saaazy813nj7Cd7yB5lC43ZZfv3qCtk43n7kkm6qmdrZp+IuIyJQ1GcvJvHC4FGvhHYvHfkgvQGxYEBmxIX6Zd2qtZdfpGu56ZD9rvvsSX35wHyV1rSxIieSfOwpobp9cPd7DdbCojuyEcMJ6jRgbjfevziAtOoQfv3DsvL2nJysa+eT9OwlwOGjvcrPjVLVPzi+Tm4JTkWGKDw8mKiSQHadq2Hm6pmf5UHs/f/P6Se559QRZCWF85tIcHAZ2nKoZfEcREZmUuoPTyZQU6dkDpcyKD2NuUsS4nXNpejT7CsZvWG9rRxe/ee0EV/zkNW761RYe21PM1QuT+ccd63j13y7hW9cvpKGtk6f2lYxbm/xhf2EdS3yY8yM4wMmdl+ewr7COTUfK+92moqGNj963HQM8+Kn1BDoNm08M3tMqU5+CU5FhcjgM71qawhP7ivnaowd6lhfWDG0O6smKRgD+9PE1hAcHsCA1kh35elooIjJVRYcGEhEcMGl6Tmua2tl6soprFiVjjBm38y7LiKaotoXyhtZxOd89r+Tx/WePEh0axP/ctJgdX7+CH79vKWuz4jDGsHpmDDmJ4fx1+5lxaY8/lNW3Ut7Q5vOElDetSGdmXCg/fuHYOYkfG9s6+dgft1PZ0M4fblvN/JRIlmfEsCVPo8hEwanIiNyyOhNjoLi2lU9cMAuAU5VNQ9q3orGNRWmRPYmVVs2IZU9BjeadiohMUcYYMiZROZkXj5TR5bZcOw5Zentb6s2Sv3+cek9fy61k5YwYHv70Bt6/OrNPIkTw/H/74NpM9hXUTqhETb50oLA7GZJvg9MAp4MvXjmHo6UNPHPwbM9zR5ebz/x1N0dKGrjngyt6/p9vyInjYHEddc0dPm2HTD4KTkVGYFFaFFv/43L2ffMqPnNJNgAnBwlOd52u4Zev5JFX3khixNnSNIvTomjtcHO66uyXlqa2TtVSFRGZQiZTrdPnDpaSFh0y6tIiw7UwNRKHgf3jMO+0rqWDA4W1bMyOO+92Ny5PJzjAwQNTtPd0f1EdDgMLfJAM6e2uW5LKnKRwfvLicTq73Fhr+Y+HD/D68Qq+/57FXDovsWfbjTnxWAtblYNj2lNwKjJCyVEuggIcxIYFEekKOG/P6emqJm761RZ++PwxCmtaSIwI7lmXk+hJ0Z9X3tiz7Av/2MvGu1+mrVOZ60REpoKM2BAKalomfG3rhtYO3sytHPchvQChQQHMSYpgb+HY91Juz6/GbWFDTvx5t4sKDeS6Jak8vqdo0pUCGooDhbXMTowgNMg3yZB6czoMX7pyDicrmnhsbzE/fuE4D+8u5ItXzOF9qzP6bLs0PZqQQCdbNO902lNwKjJKxhhmxYeRf57g9P9eziM44Ow/t4RewWm2Nzg9UXE2OO0uXr3tpOaiiohMBZmxobR3uqlobPN3U87r5aPltHe5x31Ib7dlGdHsK6gdco3MkdqcV4kr0MHyzOhBt711bSZN7V08sXdq1eK01nKgqN7n8017u3phMovSIvn2E4f4xSt5fGBNBndennPOdkEBDtbMimVznoLT6U7BqYgPDBacvplbydULk3tqpPbuOQ0PDiAlysXxsoaeJ+rdw2s2HS7D7bZsO1lF1wR/2i4iIgPLmCQZe585UEJiRDArMmP8cv6lGdHUtXT0meoyFraeqGL1zFiCA5yDbrsiM5p5yRE8sP30mLZpvJXWt1LZ2Obz+aa9GWP48lVzaWjr5PJ5ifz3DYsG7JHfmBPHiYomSuvGJyGWTEwKTkV8YGZ8GMV1LdS3njuRv665g9L6VuanRBITFgj07TkFmBkXxuN7i3nfb7ZS29xOS4cnOdKzB0t4cn8xt9y7jU//ZZcKVIuITFI95WTGOOgajeb2Tl47XsE1i5JxOMZ3SG+3penRAGNa77SioY1jZQ2sH2S+aTdjDLeuzeRgUf24zIcdL/u9w6cXj2FwCnDp3EQe++xGfvnBFQQ4Bw49NmR7hlhvPane0+lMwamID8yKD8NaWPKtF3oy33U7WloPwLzkCKJDggDP8JXePrphBmtnxbL7TA0/eP4Ydc3thAU5qWxs5+cv5eJ0GF48Usa/PbhvfH4hERHxqbSYEIyZ2D2nrx6roLXDzTV+GtILMCcpHFegg70FtWN2ju6kOxuzzz/ftLd3L08jJNDJA29NncRIB4vqcDoMC1J8nwzp7ZZlROMKPH8v9YKUSKJDA9mskjLTmoJTER+YFR/W8/pXr+X1WXe8rAGAuckRfPuGhVw8J4E1s/o+rb1mUQr/+Jf1vG9VBo/sLuRUVTM3LE8jISKYExVNLEmP4vqlqWP6JFlERMZOcICT5EjXhK51+tzBUmLDglgzM9ZvbQhwOliUGtXTqzcWtuRVEuEKGNZcy0hXYE+N8/5GSU1G+wvrmJ0YPmjQOF4cDsP6rDi25FWO+ZxjmbgUnIr4wJykCK5ckMSaWbE8f6iM8vqz8yWOljYQ4fLMK81OCOf+j685p5Zat1vXZtLqHdIbHx7MTSvSAU+5mbiwYGpV/0tEZNLKiA2loGZiBqddbstrxyu4ZG7CeYdejoelGdEcLKobs/rfW05UsS4rDucwhy7funYGze1dPL6naEzaNZ48yZDqxnS+6UhsyImnuK6VUxN4+LuMLQWnIj7gCnTy24+s4nvvWUyX2/LEvrMZ/Y6VNjAvOWJIKfnnJEX0vI4OCeT9qzMIcjpYlxVHdGggjW2dPTfr5w6WcPezR33/y4iIyJiYyLVO9xXWUtfSwSVzEwffeIwtzYimrdPNsdIGnx+7oLqZM9XNg9Y37bdd6VEsSInkr2+dmfQ9e8V1rVQ3tY97LdvBdP9/Udbe6UvBqYgP5SSGsyQ9it+9kU9eeQPWWo6VNTA3OWLwnaHP0Jro0EBmxYex/WuXc+2iZKJDPcmU6lo8vacP7y7iD5vzJ3zNPBER8ciMDaWsvo3WjomX3O61YxU4DFw4SN3P8bBsDJMiddfRHKy+aX+MMXxwXSZHSxvYM4ZzYsfDAe+1Xey91hPFrPgwUqJcbD2heafTlYJTER/7zrsX0dLRxQ+fP0ZxXSsNrZ3MTRpacAr0DPmNCfUkT4oODcIYQ1SIJzjtHtpbUN08KWrmiYiIR3fG3sIJOLT3teMVLM2IJiYsyN9NISM2hJjQQPaNQQC45UQV8eHBzPbWGB+uG5alERY0+RMj7S+sI8BhmDfEh+fjxRjDhux4tpyo1MP3aUrBqYiPLUmP5oLZ8RwuqedIsSdT79zkoWfC6+4hjfQGo926g9Xa5nastT1JNSbilxwRETnXRK11WtPUzr7CWi6ek+DvpgCeAGVpRjT7CnybFMlay5YTVWzIjhvSVJv+hAcHcP2yNJ7aX9wzkmkyOlBUx5ykiAmTDKm3Ddlx1DR3cMRb7UCmFwWnImNgXlIEBdUtfP7ve4gKCWRB6tCD0+6nua7Avv88u4PWmuYOqpvaafLWPC2obvFRq0VEZCxlxIYAE6/W6Rt5lVjLhAlOwfOgN7e8gaa2Tp8dM6+8kYqGNjbmDH++aW8f9CYvfHR3oY9aNr4majKkbhu9Q663qKTMtKTgVGQMzPPWDGtq7+KB29cOmJ23Pz953zK+/s7559Qd666RevufdnL9Lzb3LFfPqYjI5JAQHowr0EFBzcR6qPjasQqiQwNZMoHmHy7LiMJtPbU4faU7yc6GYdQ37c+itCiWpEfxwPbJmRipsKaF2uYOFk/Q4DQ5ykVWQhibTygp0nSk4FRkDHTP4XAYWJg6vA//mLAgPnlh1jlDjqJCzw7zLao9+8VGPaciIpODMWbMM/YeK23gZEXjkLd3e0vIXDg7YdilVcbSkjFIirTlRBUZsSE9w6tH48blaRwva6S4rnXwjSeYA96Af0latH8bch4bs+PZnl89ZuWEZOJScCoyBtJjQrjz8tk894WLfHbMSNfZ3tf/vmEhG3PiWJoeRd4wvoSIiIh/ZcaG9uQM8LXKxjbef+9WPvmnnUPu0TtSWk9lY9uEGtILnlrf6TEhPpt32uW2bDtZxYYs32Qj7s4lMZwHARPF/sI6Ap2GOckjSwo1HjbmxNHc3jUmSbFkYlNwKjIGjDF86co5feqW+uKY3T68fiZ//eQ61syK5UBRHW2dE68sgYiInCvD23M6FsNB/+vJw9Q2d3CyooktQyzF8drxCgAumu3/EjJvtzQjmr0+Ck4OFddR39rJhlHON+2WnRAGwMmKJp8cbzwdKKplXnIkwQETLxlSt3VZcRgDmzXvdNpRcCoyiayeGcOH1mX2vF85I4b2TjeP7y2elPNeRESmm4yYUJrbu6hqavfpcV85Ws4T+4r5zCXZRIcG8uetp4e036vHKliQEklipMun7fGFpelRFNW2UOmDkmndQc5o55t2S4gIJjw4gPzKyRWcWms5UFg3YeebdosODWJhaqTmnU5DCk5FJpEHP7WB77x7cc/7FTNiAPjKQ/u5b/MpP7VKRESGKnMMysk0tnXytUcPMDsxnC9cMYf3r8rgxSNllA4yH7K+tYPdp2u4eO7EGtLbbal33ul+H8w73XKikjlJ4SREBI/6WOAZzTQrPowTk2xY75nqZupbO1mcNrGDU/DMO91zpobmdt9lbJaJT8GpyCSWGOHirmvnAfB/L+f6NOW+iIj4XmacJzj15bzTHz1/jJL6Vu6+aQlBAQ5uXZuJ21r+tv3MeffbkldFp9tOuPmm3RalReEwsHeU807bOrvYcaraZ72m3bISwibdsN79hZ5rORmC0w058XR0WXaeqvF3U2QcKTgVmeT+5eJsHrh9LTXNHbzunTskIiITU0aMb4PT3WdquH/rKT6ybgYrvaNpZsSFcfGcBP62/cx5s52+dryC8OCAnv0mmrDgAOYkRYw6Kc7eM7W0drjZkO2b+abdZsWHUVzXQmvH5Mn7cLCojqAAh09zYoyV1TNjCHQaDe2dZhScikwBq2fGEuEK4NVjFVz3f2/wi5dz/d0kERHpR0iQk4SIYJ8M623vdHPXwwdIjnTx79fM67Puw+tmUN7QxouHy/rd11rL68cr2JgTR6Bz4n4dXJoezb7C2lHlVdh8ogqHgbVZvg1OsxLCsRZOVU2e3tP9hXXMT44gKGDi/j/vFhoUwPKMGLYoKdK0MvH/MkVkUIFOBxfNSeDlY+UcLKrnRy8c93eTRERkAL6qdfqb105wrKyB77x7EeHBAX3WXTI3kbTokAETI52oaKSotoWL5ySOuh1jaWlGNLXNHaO6XltPVLI4LYqokMDBNx6GrHhPxt78STK01+22HCya+MmQetuQE8fB4jpqm32bQEwmroDBNxGRyWB5RjRP7y/xdzNEZIIzxnwO+CzQBTxtrf2Kn5s07WTEhLBjlPPo8sob+b+X87huSQqXz086Z73TYbh1bSY/fP4YeeUN5CT2Hcb56jFvCZk5E6+ETG9LvIHUv/x5F/HhwQQFOAh0GoICnAQ5HQQFGFKiQnjvqnRSokLO2b+prZM9Z2q5/aIsn7dtljc4PTlJMvaerm6moa2TJWnR/m7KkG3Mieenm3LZdrKKaxal+Ls5Mg4UnIpMEd03SRGRgRhjLgVuAJZaa9uMMRO722yKyowN5Yl9xWw9UYXbWjq63HR2WTrdbjq8/02KdLEsI5rQoHO/qrndlrse2U9IkJNvvmvhgOd5/+oMfrrpOH/ZdoZvXd93u9eOV5CTGE66dw7sRDUvOYKbV6ZTWNNMc3sntS1uOjot7V1u2jvdtHe5qWxs42cv5XLNwmRu2ziTVTNiemqDbz9VTafbstHHyZDAMyc2OdI1aTL2bs7zzN1cMSPavw0Zhu7ETblljVyzyM+NkXGh4FRkipip4FREBvdp4G5rbRuAtbbcz+2ZlrITw3Fb+MBvt513uwCHYWFqJCtnxLJqZgyrZsSQGOnibzvOsONUDT+8ecl5S6PEhwfzjsUpPLyrkK9cM7cn0G1p7+Kt/Go+vG6GT3+vsRDgdPCj9y497zYF1c38Zdtp/rb9DE8fKGFhaiQf3TCT65emsvVEFUFOx5glfZoVHzZpap1uOlLGjLhQshPC/d2UIXMFOokLC6J4kLJIMnUoOBWZIjJiQnE6DF1uT9KIji73hE5yISJ+MQe40BjzXaAV+Ddr7Q4/t2naeefiFBIjXLitJcBhCHB6hqoGODz/dTgMp6ua2Hmqhp2na/jrW6f5w+Z8wNPrWtXYxsacOG5emT7ouT68bgaP7y3m8b3FfGBNJgDb8qto73RP2BIyw5URG8pd75jP56+YzWN7irl/yym+8tB+7n72KA7j6SkMCXKOybmzEsJ4an8J1tqe3tqJqLm9ky0nqvjQ2hkTup39SY5yUVrX4u9myDgZVXBqjPlvPMOD3EA5cJu1tth4/up/BrwDaPYu3z3axorIwIICHKTHhHC6ypM0oqapncRIl59bJSLjzRizCUjuZ9XX8Nz3Y4F1wGrgn8aYLPu2VKjGmDuAOwAyMzPHtsHTUIDTwfpByppkJ4Rz2TzPXNL2TjcHi+vYdaqGnaerKaoN4HvvWTykIGPljBjmJUfw562nuWV1BsYYXjtWgSvQwZpZsT75fSaK0KAAbl2byQfWZLD1ZBV/3HyKTUfKuKKfObm+kpUQTl1LB9VN7cSFD9yL7W9v5FbS3unmigWTbyR/SlQIhTW+qwssE9toe05/aK39fwDGmDuBbwCfAq4FZnt/1gK/8v5XRMbQysyYnuC0orFNwanINGStvWKgdcaYTwOPeIPR7cYYNxAP9CmSbK29F7gXYNWqVSOv4SE+ERTgYEVmDCsyY7id4SX2Mcbw4fUz+NqjB9lTUMuKzBheP17Buqw4XIFj05vob8YYNmTHsyE7nvrWDsL7mbfrKz0ZeyubxiU4Lalr4ScvHOf/vWsBka6hZx/edLiMCFcAq2dOvgcSqdEudpyq9nczZJyMasyftba+19swoPsGdgPwJ+uxDYg2xijFlsgY+8HNS/j7HesAqGpU2nUROcdjwKUAxpg5QBCgCvdT3LuXpREeHMBftp7mTFUzJyubpsyQ3sFEugJxOMZuGGtWgjdj7ziVk/njllM8uKuQR3cXDXmfLrfl5aPlXDo3cVJO90mOclHX0kFze6e/myLjYNR/ocaY7xpjCoAP4uk5BUgDCnptVuhdJiJjKMDpIMnbW7o5r5ItefrOKSJ9/AHIMsYcBP4OfPTtQ3pl6gkLDuDGFWk8tb+Ex/Z6gprpEpyOtfSYUAKdZlzKyXR2uXuC0gd3FQyy9Vl7C2qpamrn8vmTb0gvQKq3RFCJkiJNC4MGp8aYTcaYg/383ABgrf2atTYD+Cvwr8NtgDHmDmPMTmPMzoqKisF3EJHzSosOYUFKJL95/SS3/u4t6ls7/N0kEZkgrLXt1toPWWsXWWtXWGtf9nebZHx8aN0M2rvc/OLlPDJjQ1V+zEecDsOMuDBOjkM5mTfyKilv8CTDOlhUz5GS+sF3Al46UobTYbhkzuQMTpOjPA/dS2oVnE4Hgwan1torvDext/88/rZN/wrc5H1dBGT0WpfuXdbf8e+11q6y1q5KSNBTPJHRCgpw8OhnN/D+VZ5/gqV60igiMu3NSYpg7axY2rs8WXonW8bWiSwrPmxcek4f2lVITGgg//u+ZQQ6DQ/tKhzSfpuOlLFmZixRoUOfozqRdPecFitj77QwqmG9xpjZvd7eABz1vn4C+IjxWAfUWWtLRnMuERm64AAnN6/ylBhQcCoiIgAfWT8TgMvmTc4etIlqVkIYp6uaekq5jYW65g5ePFzGDcvSSIx0cfm8JB7bU0RHl/u8+xVUN3O8rHHSDukFSIryJJrS95npYbRzTu/2DvHdD1wFfN67/BngJJAH/Bb4zCjPIyLDlOyde6oPcxERAXjH4mQe/cwGLpmrkWq+lB0fTkeXHdNyJ0/uL6a9091T2/a9q9KpamrnlaPl591v05EyAK5cMHbldMZacICT+PAgStRzOi2MKre2tfamAZZb4LOjObaIjE53YiQlEBAREfCUWFmeGePvZkw5vTP2zogbm7m8D+0qZF5yBAtTIwFPQqv48GAe2lXIVQv7K2vsselIGTmJ4WPWrvGSHOXS95lpYvLlkxaRIQkKcBAfHkRpvT7MRURExkp3cqmxmneaV97A3oJabl6Z3jNXOMDp4MYVabx8tJzKxrZ+96tv7eCtk9WTekhvt5SoECVEmiYUnIpMYclRLko1DEZERGTMxIYFERUSOGYZex/aVYTTYbhhWd+qjDevTKfTbXlsT/81T187VkGn23Ll/Mk7pLdbapRLw3qnCQWnIlNYcmQIhTX6MBcRERkrxhhmxYeRPwY9p11uy6N7Crl0bgIJEcF91s1JimBpehQP7Sqkv3LFLx0pIzYsaEoM5U6OCqG+tZOmtk5/N0XGmIJTkSlsXVYsueWNHCqu83dTREREpqyshDBOVvg+OH0jt4Ky+raeREhvd/PKdI6WNnCouG/N084uN68cq+DSuYk4HZO/bFBqtPJo+FOX247bgwEFpyJT2HtXZhAS6OQnLxzHPYYp7kVERKaz7IRwSutbff4Fvru26WXz+h+ae/3SNIICHOfUPN15uoa6lg6umALzTeFsBQIN7fWPvPJGFn7zeZ47OPaVQRWcikxhUaGB/PvVc3npaDl/3X7G380RERGZkrqTIvlyaG9dcwcvHC7j+qWpBAX0/5U9KjSQqxYk8djeIto6u3qWbzpcRpDTwYVzpkbZoNToEEA9p/6SW94AQGbs2Gd9VnAqMsV9bONMZsaF8vrxCn83RUREZErqKSfjw+D0qQPdtU0zzrvdzSvTqW3u4OUjZ2uevnS0nHXZcYQHj6pq5ISRGOmZb6uMvf6RW9aIMWf/zseSglORKc4Yw6qZsbx4uIxP3r+T1o6uwXcSERGRIZsZF4Yx+DRj70O7CpmbFMGitMjzbnfh7ASSIoN50Du090RFI/mVTVNmSC9AcICT+PBgDev1k7zyRjJjQ3EFOsf8XApORaaBlTM8mfo2HSljx6lqP7dGRERkanEFOkmNCvHZsN688kb2nOlb23QgTofhxhXpvHqsnPL6VjYdLgPg8ilQQqa3lCiXhvX6SV55I7MTw8flXApORaaBS+YmkBLlSSbw1kkFpyIiIr7my4y9D+8u9NQ2XZ46pO1vXpmO28Kje4p46Ug581MiSfPO05wqUlTr1C86u9ycrGwkJzFiXM6n4FRkGkiJCmHrXZezNCOat/Kr/N0cERGRKSfLW+u0v5qjw9Hltjyyu5BL5iSQGOEa0j7ZCeGsyIzmz9tOs/N0NVdOoSG93VKjQ9Rz6genq5vp6LLqORUR31uZGcP+wjqVlREREfGxrIRwGts6qWhoG9Vx3syrpKy+jZsGqG06kPeuyqCwpgW3nXpDegGSo1w0tHbSOE71NsUjt8wzj3p2koJTEfGxrIQw2jrdlDXoyaOIiIgvdWcyPTHKob0P7iwgKiSQy4fZ+/nOJSm4Ah0kRASzOC1qVG2YiLqnJ5VqaO+4yvOWkclOUHAqIj42M873ddhERETEN7VO9xbU8vSBEt6/OoPggOFlRo10BXLXtfP596vn4nCcP4nSZJQS5ZlDW6xyMuMqt7yRtOgQwsapLNHUKH4kIkMyMz4UgNNVzWzI9nNjREREppDUqBCCAxwjLifT2eXmrkcOkBgRzOcuyxnRMT66YeaI9psMzvacKjgdT3nljeSM03xTUM+pyLSSEhVCkNPBKfWcioiI+JTDYZgVH8bJEd5j79t8iiMl9Xz7+oVEuAJ93LrJLynShTFQrGG946bLbce1jAwoOBWZVpwOQ2Zc6IiHHJ2qbOLDv3+LqsbRJXsQERGZirISwkZ0jy2saeYnLx7nivmJXL0weQxaNvkFBTiIDw+mRMN6x01RTQttne5xS4YECk5Fpp3ZieHsPF3DNT99nV2nh17z9HvPHOGSH73KG7mVXPuzN/j4H3fwg+eOcqSkfgxbKyIiMnlkxYdzprqZ9k73kPex1vKNxw9hDHz7hkUYM/Xmi/pKSpSLknoFp+Ml15sMabxqnIKCU5FpZ0FKJNVN7RwtbeDBnYVD2mfPmRruff1kz/vyhjZePlrOPa+e4F8f2D1WTRUREZlUZsWH0eW2FNQ0D3mf5w6W8vLRcr505RzSokPGsHWTX0qUi5JaDesdL7nlnvnTmnMqImNmQWpkz+tXjpUPWiy8rbOLn7x4nACH4fYLZ52zvq6lw+dtFBERmYy6y8mcHGI5mfrWDr75xCEWpERy2xROZuQrKVEhSog0jnLLGkmMCCYqZPzmQCs4FZlmFqaerX1WVt/GoeLzD8v9+Uu5vJFbyTevX8jX3rmg56lud5b6qqZ2BagiIiJ4hvUCQ87Y++Pnj1HR2Mb3b1xMgFNfyweTEuWioa2ThlZ97xgPeRWN4zrfFBScikw7SZHBZMSG9DyhfeVo+YDbWmt5cl8JF89J4MPrZgBwzwdX8NH1M/j5B5bzpSvnYK1n2K+IiMh0FxUaSFxY0JCSIu0tqOVP207z0fUzWZoRPfaNmwJSvA/I1Xs69qy15JU1MHsc55uC6pyKTDvGGN74ymWAJ6h8+Vg5n7t8dr/bHi1t4Ex1M5+6+GxR1KUZ0T030frWDn7y4nEOFNZxydzEMW+7iIjIRJeVEDbosN7eNU2/fNWccWrZ5Ndd67S4rpXZSeMbNE03JXWtNLV3jet8U1DPqci0dvWiZPacqeVv288A4HZbyhvOPo3ceqIKgMvm9R94RroCmRUfxoGiurFvrIiIyCTgqXV6/mG9qmk6Mt3BaalqnY657mRI41njFBScikxrn7wgiwty4rnrkQO8557NLPzm86z57kvUNXvmchwsqiMxIphk782gP4vSonjhcBkHFaCKiIiQlRBOZWP/+Rjcbsurx8pV03SEkiJdGAPFqnU65nLLPGVkxruHWsGpyDQWFODgvo+t5uvvnE9TWyctHV0AHC31JEk6WFzHorSo8x2Cpeme9Tf+asugmX9FRESmuqx4T8be3vNOy+pb+cXLuVz0w1e47b4dRIYE8K3rF6qm6TAFOh0khAdrzuk4yCtvJDYsiNiwoHE9r+acikxzgU4Hn7wwi09cMItdp2u4+ddbOVbWwJL0aPLKG7lmkKe6t67N5KUj5Ww9WUVFQxuJkQP3soqIiEx13eVkcssaqGlq54HtZ3j5aDldbsvGnDi+es08rlqYRHCA088tnZxSolwUa1jvmMstbxz3+aag4FREvIwxrJwRQ6QrgNePV3Kyogm3hVUzY8+7X2hQAJ+9NIetJ6vIq2hUcCoiItNaZmwYDgN3PXKATrclPjyI2y/M4pbVGcz09qrKyKVEhZA3xFI9MjLWWvLKG7luScq4n1vBqYj0MMYQHx7MpiNlALxvVToXzo4fdL/up8QnKprYkD349iIiIlNVUICDdy5Jpba5nQ+syeSK+UkEBWgmna8kR7l4M6/S382Y0ioa26hr6Rj3ZEig4FRE3uYDazJ5bG8R33vPYpakRw1pPkxypIvQICcnvJndXj1WzqN7ivjp+5dhLbyZV8mFs+M1t0ZERKaF//vAcn83YcpKjXbR2NZJfWsHkcp0PCbyyryZev1QrkePcUSkj9svyuLpOy9kaUb0kINJh8OQlRDGCe8wm9vu28Hje4upaGzjiX3FfOQP23kj99ynnL9+7QQ/efG4T9svIiIiU1dKVAiAkiKNIX+VkQEfBafGmC8bY6wxJt773hhjfm6MyTPG7DfGrPDFeURk4spOCD+n6HheeSMP7y4EYM+Z2nP2ufvZo/z8pVwKqpvHo4kiIiIyyXXXOi2uVVKksZJb3kCEK4CEiOBxP/eog1NjTAZwFXCm1+JrgdnenzuAX432PCIysWUnhFNU20JLexcBDk+P6+a8yp55IfsLa/tsX9PU3vP6L2+dHrd2ioiIyOSVEq2e07GWW9bI7MRwv0zH8kXP6f8CXwF6Fzi8AfiT9dgGRBtjxj/dk4iMm+6kSMfKGnB7653+8pUTWAurZ8awr7AWay0F1c0U17bwqb/s6tl356kav7RZZLoxxiwzxmwzxuw1xuw0xqzxd5tERIYjMSIYY6BYwemYOVHRyOzE8Z9vCqMMTo0xNwBF1tp9b1uVBhT0el/oXdbfMe7w3iB3VlRUjKY5IuJH2QmeeQlvHK/A3etR1coZMdy0Ip3KxnZ2nKrhwh+8woa7X+at/GoAblqRzsGiOjq63P5otsh08wPg29baZcA3vO9FRCaNQKeDxIhgSse41mlLexfu3l9oponqpnYqG9uZnTT+801hCMGpMWaTMeZgPz83AP+J5+Y2Ytbae621q6y1qxISEkZzKBHxo1nxYRgDL3rL0HxoXSY3Lk/je+9ZzDuXpBAW5ORbTxzqs8/NK9O5ZG4CbZ1ujpU2+KPZItONBSK9r6OAYj+2RURkRJKjQigZw57TprZOLvrhK/x00/RL2pjnTYaU44dkSDCEUjLW2iv6W26MWQzMAvZ5xyOnA7u9Q4SKgIxem6d7l4nIFOUKdLJqRgw7TtUQEujkq9fMI6JXivd3LU3l7zvODqh46nMXsCgtitNVniRKB4rqWJQWNe7tFplmvgA8b4z5EZ4H1Bv82xwRkeFLjXJxvGzsHmo/vLuQioY2/rajgDsvn02Ac/oUOMkt91xXf5SRgVEM67XWHrDWJlprZ1prZ+IZurvCWlsKPAF8xJu1dx1QZ60t8U2TRWSiev/qTADevTy1T2AKcNGcsyMjjn3nmp5AND0mlACH4Ywy9or4xCAjnj4NfNFamwF8Efj9AMfQlBsRmbCSo1yU1LVire+H3brdlvs2nyI8OICKhjY2n6jy+TkmstyyRkKDnKR6syKPt7F6DPAMcBLIA34LfGaMziMiE8h1S1L4yPoZfOaSnHPWrcuK63kdHODsee10GNJiQnjrZBUP7iw4Zz8RGR5r7RXW2kX9/DwOfBR4xLvpg0C/CZE05UZEJrLUqBCa27uob+30+bFfOVZOfmUT37p+IVEhgTziLYk3XeSVN5Ljp0y9MIRhvUPl7T3tfm2Bz/rq2CIyObgCnfzXDYv6XRcbFkRIoJPF/QzdzYgJ5c28SnafqWVhahQLUiP7OYKI+EAxcDHwKnAZkOvX1oiIjEBKtKdXr7SulaiQwEG2Hp4/bM4nJcrFDctS2VtQw0O7Cmlo7ThnRNhUlVfeyIacuME3HCPTZwC1iPjdnm9cyV9vX3vO8ozYkJ7XD+5S76nIGLod+LExZh/wPTy1yEVEJpUU75DTYh9n7D1SUs/mvCo+sn4mgU4HN65Ip7XDzbMHS316nomqvrWD0vpWv5WRAQWnIjKOXIFOAvtJKhAbFtTz+sXDZePZJJFpxVr7prV2pbV2qbV2rbV21+B7iYhMLClRnofapT7O2PuHN/MJCXTygTWevK7LM6KZFR82bYb2dmfqne2nTL2g4FREJoDuoTJZ8WEU1rRQ19Lh5xaJiIjIRJUYEYzDQEmt73pOKxvbeHxvMTetTCM61PPQ3BjDjcvT2HaymsKaqZ+4Ma/MG5z6qcYpKDgVkQngtg0z+Z+bFvP16+YDnmE1IiIiIv0JcDpIjHD5tNbpX7adpr3Lzcc2zuqz/N3L0wB4bM/Ur4qZW95AcICD9JhQv7VBwamI+J0r0Mn7V2f2lJc5XKzgVERERAbWXU7GF9o6u/jLttNcOjeB7IS+vYYZsaGsnRXLI7uLxqR0zUSSW95IVkI4Tod/MvWCglMRmUASI1zEhwfzVv70qikmIiIiw5Ma7aLERwmRnthbTGVjO5+4IKvf9TetSOdkZRN7C2p9cr6JKq+80a/zTUHBqYhMMLeszuD5Q2XsOVPj76aIiIjIBJUcGUJJXeuoezOttfz+zXzmJkWwcYASKtcuTiY4wMEju6fu0N7m9k4Ka1oUnIqI9PbpS7JxGHj5aLm/myIiIiITVGq0i+b2LupbOkd1nK0nqzha2sDHL5iJMf0PZ41wBXL1wmSe3F9MW2fXoMd8fG8Rv37tBM8fKiW3rGFI+/jbifImwL/JkAAC/Hp2EZG3CQsOIDHCRXGtb9PDi4iIyNTRXU6mpL6FqNDAc9Zba3n+UBnZCWHMThq4bucf3swnNiyIG5alnfd8N65I44l9xbxytIJrFiUPuN09r+bxg+eO9VnmMJAWE8Ks+HCy4sNYnhnN9UtTBwyG/SG3vAGAHD/WOAUFpyIyAaX4cB6JiIiITD3JUS4ASmpbmZcc2Wdda0cXdz1ygEe9GXYvm5fI7RdmsS4rtk9AmF/ZxEtHy/ncpTm4Ap3nPd8FOfEkRATzyO7CAYPT+7ec4gfPHeOGZal8+/qFnK5qJr+yqc/PQ6dr+OOWU7gCnVy9cOAgd7zlljcS6DTMiPNfpl5QcCoiE1BqVAiHVU5GREREBpAa7Q1O35axt6y+lTv+vIt9BbV84YrZGAx/2nqKD/x2G0vSo7j9wiyuXZRMgNPBHzfnE+AwfGj9jEHPF+B08O5lqfxxyymqm9qJDQvqs/7BnQV884lDXLkgiR+9dymBTgfRoUEszYjus11nl5srfvIaP92Uy5Xzk3D4MTNub0dL6pkZF0ag07+zPjXnVEQmnJQoF8W1LVM+ZbuIiIiMTEJ4MA5Dn5FW+wpquf4Xb5Jb1sC9H17JF66Yw+evmM3m/7iM771nMY2tnXzub3u4+Ievcu/rJ3hwVyHvWppKYoRrSOe8cUU6HV2Wp/YX91n+9P4Svvrwfi6cHc8vbl1+3gAvwOngc5fN5khJPS8cLh3ZL+9jNU3tbM6r4sLZCf5uioJTEZl4UqJDaOt0U9Pc4e+miIiIyAQU4HSQFHm21unje4t432+2Euh08MhnNnBVryGzrkAnt67NZNOXLubeD68kNdrF9545SnN7F5+4YNaQzzk/JZL5KZE83Ctr7ytHy/n83/ewckYMv/nwSoIDzj88GOCGZanMig/jp5tycbv9/yD+yf3FtHe5uXllur+bouBURCaeVO88kuJaz9PQ2uZ2vv/sEcoblCRJREREPJKjXBTVtPCD547y+b/vZWlGNI9/duM5c1C7ORyGqxYm8+CnNvDIZzbwy1tXsDA1aljnvGlFGvsKaskrb2TriSo+9ZddzE+J5Pe3rSY0aGgzJgOcDu68PIejpQ08f8j/vacP7ypkfkokC1L7v27jScGpiEw4aTGeDHyFNc1Ya/nofTv4zWsn+cvW0322q2ho80fzREREZAJIjQph68kq7nn1BLeuzeQvn1hLXHjwkPZdkRnDO5ekDPuc1y9NxWHg7meP8sn7d5AZG8r9H19DpOvcjMHnP04aWQn+7z3NK29gX2EdN604f7bi8aLgVEQmnKwET42tExVNHCyqZ19BLQCv51b2bLPzVDWrv7uJn23KpahWmX1FRESmm5zEcJwOw3/dsJDvvnsRQQFjH9okRrq4cHYCm46UER8RzF8/ufac5EhD4XQYPn/5bI6VNfDsQf/1nj60qwinwwxaSme8KDgVkQknPDiA5EgXJyoaeepAMQEOw20bZrKvsJaapnYA9noD1v/ddJwP/nabH1srIiIi/vDpS7LZ/NXL+Mj6meNaM/TTl2SzLiuWv3xiLYmRQ0um1J/rlqSSnRDGz1467pfe0y635dE9hVw6N4GEiKH1OI81BaciMiFlJ4ZxoqKJN45Xsi4rjqsWJmEtHCyuAzy1yQCCAxycqmqmqa3Tn80VERGRceYKdPbUOx1P67Li+Psd68mIHV1NUKfDcOflszle1sjTB0p81LqhezOvkrL6Nm5a4f9ESN0UnIrIhJSdEM6J8kZOVjYyNzmiJ7nBm3mVlNS1kFveyMoZMfzslmUAnKho9GNrRURERIbvuiWp5CSG8/OXcuka597Th3cVEhUSyGXzE8f1vOej4FREJqTZieE0tnXS2uFmVnwYsWFBJEYE85vXTvK+32zleFkDOQnh5CRGAJBXruBUREREJpfuuae55ePbe1rf2sHzh0q5YVnqkMrfjBcFpyIyIa2YEdPzOis+rM+6guoWaps7mJscwYy4UAIchlwFpyIiIjIJvXNxCnOSwvnZpuPj1nv69P4S2jrdE2pILyg4FZEJqneNslkJnuD0wtkJACzPjOYdi5N5/+oMAp0OZsWHDdhz2t7ppqxe9VFFRERkYnI4DJ+/fA4nKpp4an/xuJzz4V2F5CSGsyR9eHVex9rQKsWKiIwzp+Ns1r2kCE+yg++8exFfuGL2OQkIchLDOVra0O9xfvTCMe59/SQ7v34F8UOsfSYiIiIynq5dlMy85Ah+9lIu1y1J7fM9yNfyK5vYebqGr14zb1yzHA+Fek5FZMJ6/LMb+fF7l+LwfkCHBDn7zYw3OzGc/Mom7npkPxUNbX3Wbc7z1Eb9586CsW+wiIiIyAg4vHNPT1Y08cS+ojE91yO7C3EYeM/yiVHbtDcFpyIyYS3NiOamlYPPhchODAfgb9sL+PVrJ/qs637y+MTe8RkmIyIiIjISVy9MJjshjAd3Fo7ZOdxuyyO7i7hgdoJfyvAMRsGpiEx6s70ZewFyyxvp6HLT0eXGWttTD/VkZRNut6W1o4sDhXXnHOPN3EpePVY+bm0WERER6c3hMFw8J5Fdp2to6+wak3Nsy6+iqLaFm1ZMvF5TUHAqIlNAVsLZbL478qu5/U87ue2+7az//ss0tHYyOzGc9k43xXUtPLirkHf94k1+9Pyxnn06u9x86Pdvcdt9O/zRfL+paGjrCd5FRETE/9Znx9HW6WbvmdoxOf5DuwqJCA7g6oXJY3L80VJwKiKTnivQyZtfvZRffXAFLR1dvHqsgs15VZR6s/ReOs9TXDq/somC6mYA7nk1r2d+6uu5FT3HsnZ8C2D702U/fpVLf/Sqv5shIiIiXmtmxmIMbD1Z5fNjN7V18tzBUq5bmoIrcOLUNu1NwamITAnpMaFcMDv+nOx2c5MiuNE7dGXHqZqegNRt4fG9RXR2ufnJi8d7tq9v6Ry/RvuRtZaGVs/vWtfS4efWiIiICEBUaCALUyPZNgbB6bMHS2lu75pwtU17U3AqIlNGhCuQZRnRPe8XpUXy/BcvYm6SZ07qz1/K5dE9RSzNiGZpehRP7Cvm8b3FHCyq57olKQAU1jb7o+njrvdw3tyy/svwiIiIyPhbnxXH7jO1tHb4dt7pQ7sKmBkXysoZMT49ri+NKjg1xnzLGFNkjNnr/XlHr3V3GWPyjDHHjDFXj76pIiKDu3VNJtcuSiYuLIh1s+IAMMbwH9fO69kmMSKYqxYms7+wjl++mses+DBuvzALgKKaFr+0e7ztPFXT83qgGrEiIiIy/tZlxdHe6Wb3mZrBNx6iwppmtp2s5qYV6ROutmlvvug5/V9r7TLvzzMAxpgFwC3AQuAa4B5jzMQc2CwiU8pNK9P51YdW8sznL+TLV83tWf6pi7NZPdPzpDAxIpgr5icBcLKiiRuXp5EeEwJAUe3kCk4rG9v42qMHaGob3nDk/UW1hAcHEB4cwDEFpyIiIhPG6lmxOAxsO1nts2O+5T3W1YsmZiKkbgFjdNwbgL9ba9uAfGNMHrAG2DpG5xMR6SMp8tzaXRmxoew4VUNihIs5SeHcujaTIKeDj10wi7AgJyGBTgonWc/pcwdL+etbZ6huamdJejSfviR7SPsdKq5nQWokHV1u8sobx7iVIiIiMlSRrkAWp0Wx7UQVXOmbYx4sriMk0El2QrhvDjhGfNFz+q/GmP3GmD8YY7oHMKcBBb22KfQuExHxm0hXIABBAQ6MMXzvPYv51vULCQ8OwBjDjLhQ3syt5NbfbqOqsc3PrT2/xrZOPvi7bXzj8YOAJ8nB/zx3lMohtLvLbTla0sDC1EhmxYepnIyIiMgEsy4rjr0FtbS0+2be6cGiOhakRp6TOHKiGTQ4NcZsMsYc7OfnBuBXQDawDCgBfjzcBhhj7jDG7DTG7KyoqBh8BxGREcqIDQUgOKD/j77ZSREcK2tgy4kqntxXPJ5NG7bvPHWYzXlVuN9W+eaxPUWAp47Z5/++p9/SOPmVjbR0dLEwNYqs+DBK61v7DAv+6kP7eWKC//4iIiJT2brsONq7fDPv1O22HCquZ1FqpA9aNrYGDU6ttVdYaxf18/O4tbbMWttlrXUDv8UzdBegCMjodZh077L+jn+vtXaVtXZVQkLCaH8fEZEBfWT9DP7fdQv44LrMftfPSTw71KVxmHM4x1NdcweP7Dn3IzXCFcDmvEoAXjpSxuN7i9l5+uxNzVrLh373Fu/6v80ArJoRQ5Z3eM+pKk/vaXVTO//YWcCdf9vj0xIzzx8q5cGdBdOqjqyIiMhIrZ4Zi9Nh2Hpi9CVl8quaaG7vYmFalA9aNrZGm603pdfb9wAHva+fAG4xxgQbY2YBs4HtozmXiMhoBTodfOKCWQQH9J+fbba35Ax4EiVNVE8fKKG9082fP7GGxWlR/O4jq/jrJ9dyydxE8io880fL6lsB+OOWU3R5u1d3n6nhzbxKWjq6yE4IY2Z8GLPiw4Czv++Borqe8zx/sHRU7XzxcFnPMON/+fMu/v2h/fx52+lRHVNERGQ6CA8O8Mw79UG904Pee/ui1CkenAI/MMYcMMbsBy4FvghgrT0E/BM4DDwHfNZa69tCPSIiPpadENbz+pE9Rdzzap4fWzOwzScqSYsO4YKceJ783AVcsSCJjTnxzE4Mp7Cmheb2TsrqPUHh0/tLyP7PZ9hyopL7Np8CICM2hK+/cwEAM+PCCHAYnjtUirWWA4W1PecpHEXm4hMVjdz+p5188R97qWs+2wP76jFN3xARERmK9dlx7Cuspbl9dKO5DhXXExTgYHbSxE6GBKMMTq21H7bWLrbWLrHWXm+tLem17rvW2mxr7Vxr7bOjb6qIyNjKSQznBzcv4YKceAB+8NyxCTkM9VBRHYvTos6pUzY7MRxrIa+8kbL6Vq5bcnZwy388fICn9pdw52U5vPGVy7h0XiIAIUFO7rx8Nk/vL+H5Q2XsL6xjVnwYSZHBFA8jON19poaSurPbP+4ddny4uL6nNzYxIphDxXX97t+tpqmdG+/Z7JMnxdOVMea9xphDxhi3MWbV29apBrmIyCSxLiuOji7LrtOjm3d6sKiO+ckRBDp9kQt3bE38FoqIjBNjDO9blcHtF2X1LCtvmFhZextaOzhV1cyitHOTGnQ/Ed2eX02n27J6Zix/u30doUFOzlQ3kxEbwuevmHPOfp+9NIeZcaH88pU8jpY2sCAlkpSokD7BZn/t+MC92/jrW6dxuy0f/f12fvT88Z71Tx3wPKusamrntePlANyyJpOy+jYWf/P5AbMhv55bwe4ztbgCVRp7FA4CNwKv916oGuQiIpPLqhkxBIxy3qm1loNFdZNivikoOBUROcfFcxJ44Pa1AOSWTawaoIeL6wH6vcnMiAvD9CranRQZzPrsOC6c7ekJXjcrrt8U8k6H4RMXzOJAUR1nqpuZkxRBarSLktrWAdtxvKyBrSer+NqjB3n6QAkNbZ0cKq7jVGUT33riECcrmrhhWSoA9285zYKUSDZkxwHQ0NY5YG3VV46WExcWxJJJchOdiKy1R6y1x/pZ1VOD3FqbD3TXIBcRkQkoLDiAJelRbB3FaKLCmhbqWzsnxXxTUHAqItKv2Yme5Ei55Q0Tamhvrjeom5cccc66QKeDpAgXe7xp55MiXQA9AemS9IFvTBfPSex5PScpnJSoEIrrWgb83asa23te/+ylXMAzz/TbTx7ij1tOAfCZS3LYmONJhf/xC2axPDOapd42VDe1n3PM9k43rx2v4OI5CTgmeB22SUo1yEVEJpn12XHsL6zrU/JtOLqn1vQ34moiUnAqItKP+PAgokMDefloOfO/8Rz7eyUKGk97C2r59F92cay0AYDi2hYCHIbECFe/26dEu6jyBn7JUZ5t3rvKU9mrdwD6dhmxIT2v5yRHkBLlorXDTW1z/+VkuoPL5EhXTy9oR5dlS6+hR3OSwvnvGxbx8Y2zuH5pKsEBTn77Ec8UyMq3Bae/ee0Ec77+LDXNHbzL2+MqAxukBrkvjq8a5CIiE8D6rHi63JYdp6pHtP/BojoCHIY5Sec+1J6IFJyKiPTDGMPsxHDeyK2ktcPNWydHdlMYrXteyePZg6Xc/qedAJTUtZIU6ep3eC5AarQnyAwLcpLkDWAvnZvIqbvfSWZc6IDnMcbgCvTcEmbEhvYcp9g77/SVo+V9su52B8B3Xj4bgNiwIADaOt28e1kqm750EcYYshLC+ca7FhAU4Dl2jHe7t885/ccOT4deaJCTi2er5vVgzleD/Dy7qQa5iMgks3JGDIFO0zNlZ7gOFtczOyli0uRyUHAqIjKAnMSzTxmPensux9MDb53hhcNlOAycqW7mU3/exdP7S0iN7r/XFCDNG1TOTY4Y9tDY579wEffdtpoAp+NscFrbyiO7C/nYH3fwi1dye7atamwnNMjJrWszee3fL+HJz11Airen9qqFyX2uXW+BTgfRoYF9hgUDBAU4SIgI5ol/vUBDeseOapCLiEwyIUFOlmVEj2jeqbWWQ0V1LEqdHEN6QcGpiMiAZieerQd2rKx+XM99qrKJ/3z0AADfe89iAJ47VEp7l5uUqJAB9+sOELuH9A7HjLiwnhIzqd79i2tbuPvZowDkVzb1bFvd1NbTWzojLoy06BAe++xGPrZxJhfPOX9PW1xYEFVNfXtOS+pauWZhMjmJE78G20RnjHmPMaYQWA88bYx5HlSDXERkslqXFcfBojoaWvufajOQ0vpWqpraWXyenBMTjYJTEZEB9C5WnVvWSJd7/BIjdc8teeJfN3LTyvQ+67p7NfvTnb8oKiRoVOePDw8m0Gl4+Wh5Tzmd3r3HVU3txIUH99knKdLFN9+1kLDggPMeOy48mMpePafN7Z3UtXSQcp4eYRk6a+2j1tp0a22wtTbJWnt1r3WqQS4iMsmsz4qjy23ZeWp49U4PFnkz/E+STL2g4FREZEDdGXuTIoNp63Rz0JvxbjzsOl1DpCuARalRBDodfOri7J45oefLHvzOJSnkJIZzR69arSPhcBiSIl28dtyTDOe2DTMprGnpmXda3dROXNjIAuD48CCqGtt4/XgFB4vqKKnzlKxJGUFvr4iIyFS3YkYMQU7HsIf2Hiyqw2FgfsrkSIYECk5FRAaUFBnMnZfP5me3LMfpMLx4uGzczr3rdA0rZ8T0zL/8j2vn8dCnNgCwzlsvtD9JkS42feliZsWHjboNqd7hw/OSI7jMO9z39VxPsFrV2N4zrHe44sKCOVHRxEf+sJ3r/u9NnthbDHDe4coiIiLTlSvQybLMaLYNMzg9VFxHdkI4oUHnH9E0kSg4FREZgDGGL105h3VZcayZGTtuwWlbZxcnKhpZlNZ3GM6itCiO/Nc1XDp34JIwvmTx9NBetySFDdlxzEuO4O5nj9La0eXpOQ0fWXC68G2JGe7fegpQz6mIiMhA1nvnndYPY97pgaK6c75LTHQKTkVEhmDVzBjyKhrp7HKP+blOVTbjtvSbHCgkaPxSwUeFBAJww7I0ApwOvnTlHIpqW/jLttO0d7l7hj0P1/tXZ/CbD6/kvttWsyQ9itrmDoIDHOo5FRERGcC6rDjcFrYPsaRMeUMrZfVt5zwQnugUnIqIDEFadAhdbtszP3Io8iubeO5g6bDPlVvuSTzk78y1379xCfd/fA0ZsZ76qBfNSSAsyMkPnj8GwJIRZv8zxnD1wmQunZfIvGRPgLs8M7qnFqqIiIj01X2fHOrQ3kPFnmRI6jkVEZmC0mM8AVpRbcuQti+qbeG9v97Cp/6yi+cOlpx32397cB8b736Z7fmep6F55Y0YA9kJ/g1OEyKC+5SFcQU6uXx+Eu2dnt5jX7QvLTrUZ8cSERGZqlyBTlZmxgw5KdIhbxJH9ZyKiExBaTGeIaeFNf0Hp263pby+tSeT7j92FFDd1M6MuFB+8/rJAY9rreWp/cUU1bbwxy35AOSWN5IRE4orcPyG8A7Vl6+aA3hqlTq9yZpGY703udM7FqeM+lgiIiJT2bqsOA6X1FPb3D7otgeL6pkVH0aEK3AcWuY7Ck5FRIYg1VuD8/G9RVR4634+ua+Y373hCTz/sDmfNd97iZt/vZXOLjcvHy1jRWYMa2fFUnye3tbCmhZaOzw9kfsKPE85T5Q3MtvPQ3oHMiMujEc/s4G/3bHOJ8dbMyuW/d+6io058T45noiIyFR1+fxErIW/bS8YdNuDxXWTrtcUFJyKiAxJcICnF/ON3Eq+9cQhAD73tz185+kjbDlRyW+9Qequ0zX87KVcDhbVc+m8RJKjQihvaKNjgERK3bVTb1iWSlFtC6V1rZysaPL7fNPzWZ4Zw5wk39VMi5xkT3VFRET8YVFaFBfPSeB3b5ykub1zwO1qm9sprGmZdPNNQcGpiMiQddcOLW9opbz+bGKkz/99L2X1bfz2I6tYkh7FL1/JAzxDVlOiXFhLT2/r2+0vqsPpMLx/VQYAD+8upL3LPaGDUxEREfGPOy/PoaqpnQfeOjPgNj3JkFIVnIqITFn/+Jd1rJkZS1VTe09CgoSI4J7Ac3lmNOu9qd6dDsOClEiSvbU7+8vy29rRxYM7C9mQHceaWbGkRrn4oTcTroJTERERebuVM2LZmBPHr187SWtHV7/bHJikyZBAwamIyJAlRrhYnhlNYU0Lh0vqCXQa3rUkFfDUBI0LC2JZRjQAsxPDcQU6SfEGp6X9BKdP7S+hsrGNz16aQ4DTwcc2zupZl63gVERERPpx52WzqWxs4+/b++89PVhUR1p0CDFhQePcstEL8HcDREQmk4zYUNo73RwrbSA6NIg5SZ4gMicxHGMMyzKjAVjsneeREunJ8rvnTA3XLkrG0SvD7YHCWsKDA1gzMxaAj22cSXCgg44uq3mYIiIi0q+1WZ4RV7967QS3rMk8J7v/oeL6nu8hk416TkVEhiEz1lOX80BhHTGhgT09nDneOp0pUSF87rIcPrRuBgCRIZ5ngL97M5/H9hb1OdaR0gbmJkf0BKwBTgcfWT+TT1wwCxEREZGBfP7y2ZTVt/HgrsI+yxtaO8ivbGJR2uQb0gsKTkVEhiXDG5xWNbUTHRLE7MRwgpyOPjeBL181l6Xe4b3GGH556woAXjte0bPN8bIGdp+uYV6y77LeioiIyPSwITuOlTNi+NUrebR3nq0IcNibDGmhek5FRKa+5EhXz+vo0ECiQ4N48UsXccuazAH3eeeSFK5bksJbJ6ux1lLV2MZV//s6nW6r4FRERESGzRjD5y7LobiulUd2n+09PTiJM/WCglMRkWEJCXIS6fIM1Y0O9cwLnREXRqDz/B+na2fFUlrfygX/8wovHy3vWX7J3MSxa6yIiIhMWRfPSWBpehS/fDWvp576oaI6kiKDSYgI9nPrRkbBqYjIMCV5e09jQoeeBe+dS1K5Yn4iRbUt/PtD+wkOcHD8O9f2DBMWERERGQ5P7+lsCqpbeGyPJ6/FweK6SdtrCgpORUSGLTLE02MaFTr0jLqxYUH87qOref+qDADmpUQSFKCPYBERERm5y+cnsiAlkntePUFDawd55Y2Tdr4pqJSMiMiwBXuDyuH0nHb7/o2LuXBOPNkJqmMqIiIio2OM4c7LZ/Opv+zih88fw21hUerkzNQLCk5FRIatOzgdSS1Sh8Nw3ZJUXzdJREREpqmrFiQxNymCP209DcDi9Mnbc6oxZSIiwxQc4Cl2bbF+bomIiIhMdw6H4XOX5wAQFxbUp7LAZKPgVERkmK5YkARAVryG5oqIiIj/XbsohXnJEayaGYMxxt/NGbFRD+s1xnwO+CzQBTxtrf2Kd/ldwCe8y++01j4/2nOJiEwEN69M55K5CcSHT8407SIiIjK1OB2GBz+1Hqdj8gamMMrg1BhzKXADsNRa22aMSfQuXwDcAiwEUoFNxpg51tqu0TZYRGQiUGAqIiIiE0nECHJhTDSjHdb7aeBua20bgLW2u7L8DcDfrbVt1tp8IA9YM8pziYiIiIiIyBQ12uB0DnChMeYtY8xrxpjV3uVpQEGv7Qq9y85hjLnDGLPTGLOzoqJilM0RERERERGRyWjQYb3GmE1Acj+rvubdPxZYB6wG/mmMyRpOA6y19wL3AqxatUqpL0VERERERKahQYNTa+0VA60zxnwaeMRaa4Htxhg3EA8UARm9Nk33LhMRERERERE5x2iH9T4GXApgjJkDBAGVwBPALcaYYGPMLGA2sH2U5xIREREREZEparSlZP4A/MEYcxBoBz7q7UU9ZIz5J3AY6AQ+q0y9IiIiIiIiMpBRBafW2nbgQwOs+y7w3dEcX0RERERERKaH0Q7rFRERERERERk1BaciIiIiIiLidwpORURERERExO+MJ3/RxGCMqQBO++hw8XgyB8vI6Rr6hq7j6Okajt50vYYzrLUJ/m7EZObje/NkNF3/7YyErtXQ6VoNj67X0E2GazXgvXlCBae+ZIzZaa1d5e92TGa6hr6h6zh6uoajp2soMjL6tzN0ulZDp2s1PLpeQzfZr5WG9YqIiIiIiIjfKTgVERERERERv5vKwem9/m7AFKBr6Bu6jqOnazh6uoYiI6N/O0OnazV0ulbDo+s1dJP6Wk3ZOaciIiIiIiIyeUzlnlMRERERERGZJKZccGqMucYYc8wYk2eM+Q9/t2ciM8b8wRhTbow52GtZrDHmRWNMrve/Md7lxhjzc+913W+MWeG/lk8cxpgMY8wrxpjDxphDxpjPe5frOg6RMcZljNlujNnnvYbf9i6fZYx5y3ut/mGMCfIuD/a+z/Oun+nXX2ACMcY4jTF7jDFPed/rGooMQT//dowx5rvGmOPGmCPGmDt7LZ/Wn+H9XKs3jDF7vT/FxpjHvMt1rc69VpcbY3Z7r9Wbxpgc73J9JtPv9brMe70OGmPuN8YEeJdP678tY8wpY8wB79/RTu+yKfO9c0oFp8YYJ/BL4FpgAfABY8wC/7ZqQvsjcM3blv0H8JK1djbwkvc9eK7pbO/PHcCvxqmNE10n8GVr7QJgHfBZ79+cruPQtQGXWWuXAsuAa4wx64D/Af7XWpsD1ACf8G7/CaDGu/x/vduJx+eBI73e6xqKDM3b/+3cBmQA86y184G/e5frM/xt18pae6G1dpm1dhmwFXjEu0rX6ty/q18BH/ReqweAr3uX6zPZo+d6GWMcwP3ALdbaRXhqLX/Uu53+tuBS77+77pIxU+Z755QKToE1QJ619qS1th3PzeQGP7dpwrLWvg5Uv23xDXg+DPD+9929lv/JemwDoo0xKePS0AnMWltird3tfd2A50M1DV3HIfNei0bv20DvjwUuAx7yLn/7Ney+tg8BlxtjzPi0duIyxqQD7wR+531v0DUUGdTb/+14fRr4L2utG8BaW+5dPq0/wwe4Vt3rIvF85jzmXaRrde61skCk93UUUOx9Pe0/k/u5XnFAu7X2uPf9i8BN3tfT+m9rAFPme+dUC07TgIJe7wu9y2Tokqy1Jd7XpUCS97Wu7SC8w3CWA2+h6zgs3qE8e4FyPDegE0CttbbTu0nv69RzDb3r6/DcxKa7nwJfAdze93HoGooMxU/p+28HIBt4vzFmpzHmWWPMbO/y6f4Z/lPOvVbd3o2n56be+17X6txr9UngGWNMIfBh4G7vcn0mn3u9KoEAY0x3z+DNeEYzgP62LPCCMWaXMeYO77Ip871zqgWn4kPWk8pZ6ZyHwBgTDjwMfKHXjRnQdRwKa22Xd5hTOp4REPP826LJxRhzHVBurd3l77aITCbn+bcTDLR6h8z9FvjDuDdughnC58wHgL+NY5MmrPNcqy8C77DWpgP3AT8Z98ZNQP1dL+93p1uA/zXGbAcagC4/NXGiucBauwLPkN3PGmMu6r1ysn/vDPB3A3ysiLNPVcDzRbfIT22ZrMqMMSnW2hJvt3/3UCZd2wEYYwLxBKZ/tdZ2z7XRdRwBa22tMeYVYD2eoScB3qfIva9T9zUs9CZHiAKq/NLgiWMjcL0x5h2AC8+wsZ+haygymHP+7Rhj/oKnd6H78/xRPIEETO/P8H6vlbX2Q8aYeDwPFt/Ta3tdq77X6mk8c5jf8m7zD+A57+vp/pk84N8WcCGAMeYqYI53++n8t4W1tsj733JjzKN4/u1Nme+dU63ndAcw23gyVAbheeLyhJ/bNNk8wdkJ5x8FHu+1/CPerF/rgLpewwemLe+ckN8DR6y1vZ+A6joOkTEmwRgT7X0dAlyJZ+7uK3iG8cC517D72t4MvGynecFma+1d1tp0a+1MPJ97L1trP4iuoch5DfBv50N45k1e6t3sYqB73tu0/Qw/z7UCz+fIU9ba1l676Fr1ulZ45v5FGWO6A6zuex1M88/kgf62jDGJ4MlmDHwV+LV3l2n7t2WMCTPGRHS/Bq4CDjKFvndOqZ5Ta22nMeZfgecBJ/AHa+0hPzdrwjLG/A24BIj3zn/4Jp75D/80xnwCT2a093k3fwZ4B5AHNAMfG/cGT0wb8cwbOeCdMwnwn+g6DkcKcL8327YD+Ke19iljzGHg78aY7wB78DwEwPvfPxtj8vAk9LrFH42eJL6KrqHISNwN/NUY80WgEc9cQdBn+EBu4ez8yW66Vr14v6PeDjxsjHHjyaD+ce9qfSb379+9Q34dwK+stS97l0/nv60k4FFvvqwA4AFr7XPGmB1Mke+dZho9mBEREREREZEJaqoN6xUREREREZFJSMGpiIiIiIiI+J2CUxEREREREfE7BaciIiIiIiLidwpORURERERExO8UnIqIiIiIiIjfKTgVERERERERv1NwKiIiIiIiIn73/wHXLC/Z+WNN6AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1152x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stock_lower_array=np.argsort(np.sum(stock_day_change_test,axis=1))[:3]\n",
    "#stock_lower_array\n",
    "def show_buy_lower(stock_ind):\n",
    "    \"\"\"\n",
    "    :param stock_ind: 股票序号，即在stock_day_change中的位置\n",
    "    ：return:\n",
    "    \"\"\"\n",
    "    _, axs =plt.subplots(nrows=1, ncols=2, figsize=(16.0, 5.0))\n",
    "    #np.cumsum: 序列连续求和\n",
    "    axs[0].plot(np.arange(0, view_days-keep_days),stock_day_change_test[stock_ind].cumsum())\n",
    "    \n",
    "    cs_buy=stock_day_change[stock_ind][view_days-keep_days:view_days].cumsum()\n",
    "    axs[1].plot(np.arange(view_days-keep_days, view_days), cs_buy)\n",
    "    return cs_buy[-1]\n",
    "\n",
    "profit=0\n",
    "for stock_ind in stock_lower_array:\n",
    "    #print(stock_ind)\n",
    "    profit += show_buy_lower(stock_ind)\n",
    "print('买入第{}只股票， 从第454个交易日开始持有盈亏：{:.2f}%'.format(stock_lower_array, profit))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bae0012f",
   "metadata": {},
   "outputs": [],
   "source": [
    "gamblers=100\n",
    "def casino(win_rate, win_once=1, loss_once=1, commission=0.01):\n",
    "    my_money=1000000\n",
    "    play_cnt=10000000\n",
    "    #commission: 手续费简单设置为0.01 即1%\n",
    "    commission=commission\n",
    "    for _ in np.arange(0,play_cnt):\n",
    "        # 使用伯努利分布，根据win_rate来获取输赢\n",
    "        w=np.random.binomial(1, win_rate)\n",
    "        if w:\n",
    "            # 赢了，+ win_once\n",
    "            my_money+=win_once\n",
    "        else:\n",
    "            my_money-=win_once\n",
    "        my_money-=commission\n",
    "        if my_money<=0:\n",
    "            break\n",
    "    return my_money\n",
    "\n",
    "# 假定天堂赌场，没有老千，也没有抽头\n",
    "# 100个赌徒进场，胜率0.5，赔率1，还没手续费\n",
    "heaven_moneys=[casino(0.5,commission=0) for _ in np.arange(0, gamblers)]\n",
    "print(heaven_moneys)\n",
    "# 假定天堂赌场，有老千，没有抽头，导致胜率只能达到0.4\n",
    "# 100个赌徒进场，胜率0.4，赔率1，还没手续费\n",
    "cheat_moneys=[casino(0.4,commission=0) for _ in np.arange(0, gamblers)]\n",
    "# 假定天堂赌场，没有老千，手续费0.01的情况\n",
    "# 100个赌徒进场，胜率0.5，赔率1，还没手续费\n",
    "cheat_moneys=[casino(0.5,commission=0.01)  for _ in np.arange(0, gamblers)]\n",
    "\n",
    "plt.hist(heaven_moneys,bins=30)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42d39808",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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